Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Rotenberg, Ari
Master of Science - MSc
University of British Columbia
Over the past decades, invasive and non-invasive neuromodulation approaches have emerged to manage neurologic and psychiatric conditions, along with powerful functional neuroimaging methods that provide insights to the physiologic bases for cognition and behavior. However, new capabilities realized by neurotechnology also introduce new concerns. Neurotechnology has proliferated into industries such as defense, advertising, and retail, evolving in ways that may impinge on the privacy of thought and create injustices in human performance. In these contexts, newfound access to the brain raises broad concerns for human rights. In this thesis, I examine 779 patents granted by the USPTO between 2016 and 2020 as a publicly accessible record of inventions early in commercial development to understand the characteristics of neurotechnology innovation and assess their ethical and social implications. By applying qualitative methods to existing patent infrastructure, I develop a perspective of an innovation landscape rooted strongly in healthcare. Neuromodulation is most prominent, with conditions affecting the injured or aging brain a substantial focus. Neurotechnology across other industries such as entertainment and finance raise concerns about consent and coercion. I further consider how these inventions may support or impede the mental protections proposed by neurorights advocates. With some concerns identified in past work and in this thesis, anticipating that more ethically fraught innovation may come down the commercial pipeline is a critical exercise. Such a practice is also fundamental to the anticipatory tenet of neuroethics. To this end, I conclude by welcoming patent experts into the neuroethics circle, and at the same time urge ongoing attention to the patent landscape as a means of informing outreach and ensuring long term societal benefits.
THE NEUROTECHNOLOGY PATENT LANDSCAPE IN A TIME OF NEUROETHICS: 2016-2020 by Ari Rotenberg B.A., University of British Columbia, 2021 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2023 © Ari Rotenberg, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: The Neurotechnology Patent Landscape in a Time of Neuroethics: 2016-2020 Submitted by Ari Rotenberg in partial fulfillment of the requirements for the degree of Master of Science in Experimental Medicine. Examining Committee: Dr. Judy Illes, Professor, Neurology, University of British Columbia Supervisor Dr. Zelma Kiss, Professor, Neurosurgery, University of Calgary Supervisory Committee Member Dr. Paul Pavlidis Professor, Psychiatry, University of British Columbia Supervisory Committee Member iii Abstract Over the past decades, invasive and non-invasive neuromodulation approaches have emerged to manage neurologic and psychiatric conditions, along with powerful functional neuroimaging methods that provide insights to the physiologic bases for cognition and behavior. However, new capabilities realized by neurotechnology also introduce new concerns. Neurotechnology has proliferated into industries such as defense, advertising, and retail, evolving in ways that may impinge on the privacy of thought and create injustices in human performance. In these contexts, newfound access to the brain raises broad concerns for human rights. In this thesis, I examine 779 patents granted by the USPTO between 2016 and 2020 as a publicly accessible record of inventions early in commercial development to understand the characteristics of neurotechnology innovation and assess their ethical and social implications. By applying qualitative methods to existing patent infrastructure, I develop a perspective of an innovation landscape rooted strongly in healthcare. Neuromodulation is most prominent, with conditions affecting the injured or aging brain a substantial focus. Neurotechnology across other industries such as entertainment and finance raise concerns about consent and coercion. I further consider how these inventions may support or impede the mental protections proposed by neurorights advocates. With some concerns identified in past work and in this thesis, anticipating that more ethically fraught innovation may come down the commercial pipeline is a critical exercise. Such a practice is also fundamental to the anticipatory tenet of neuroethics. To this end, I conclude by welcoming patent experts into the neuroethics circle, and at the same time urge ongoing attention to the patent landscape as a means of informing outreach and ensuring long term societal benefits. iv Lay Summary Neurotechnology opens a window to the brain and by extension the mind, offering potential to unveil the core of human experience. Although the products of neurotechnology innovation hold promise in healthcare to help those suffering from brain diseases such as Parkinson’s and drug-resistant epilepsy or depression, they may also be used in exploitive and harmful ways impinging on human privacy and thought. Scholars in the field of neuroethics aim to prevent these harmful outcomes. Many neuroethicists actively partner with policymakers and neurotechnology developers to promote responsible innovation practices and cultures. Others advocate for legal protections for the mind. In this thesis, I examine 779 patents issued by the USPTO between 2016 and 2020 to characterize technical features in neurotechnology innovation and their associated ethical concerns. My findings shed light on the current patent landscape, highlight foreseeable tensions human rights, and support the importance of neuroethics values in commercial innovation. v Preface This thesis is based on original, unpublished work conducted by the author, A. Rotenberg, as part of an international research collaboration co-chaired by Dr. Judy Illes of the University of British Columbia and Dr. Tade Spranger of the University of Bonn. vi Table of Contents Abstract ........................................................................................................................................ iii Lay Summary ................................................................................................................................ iv Preface ............................................................................................................................................ v Table of Contents .......................................................................................................................... vi List of Tables .............................................................................................................................. viii List of Figures ............................................................................................................................... ix List of Abbreviations ..................................................................................................................... x Acknowledgements ....................................................................................................................... xi Dedication .................................................................................................................................... xii Chapter 1: Introduction ................................................................................................................ 1 Chapter 2: Background ................................................................................................................. 5 2.1 Neurotechnology ................................................................................................................... 5 2.2 Neuroethics and Responsible Innovation ............................................................................ 10 2.3 The Patent Landscape .......................................................................................................... 14 2.4 The Neuroethics Challenge ................................................................................................. 17 Chapter 3: Research Methods .................................................................................................... 18 3.1 Creation of the Database ...................................................................................................... 18 3.2 Guided Review .................................................................................................................... 23 3.3 Patent Characterization ........................................................................................................ 27 Chapter 4: Results ....................................................................................................................... 30 vii 4.1 Patent Search ....................................................................................................................... 30 4.2 Landscape Characterization ................................................................................................. 31 4.3 Ethical Analysis ................................................................................................................... 48 4.4 Summary .............................................................................................................................. 52 Chapter 5: Discussion .................................................................................................................. 53 5.1 Major Classifications ........................................................................................................... 53 5.2 Landscape Themes .............................................................................................................. 56 5.3 Ethics Themes ...................................................................................................................... 63 5.4 Limitations ........................................................................................................................... 66 5.5 Summary .............................................................................................................................. 68 Chapter 6: Conclusion ................................................................................................................. 69 6.1 Synopsis ............................................................................................................................... 69 6.2 Future Directions ................................................................................................................. 70 Bibliography ................................................................................................................................. 72 viii List of Tables Table 1: Numbers of patents granted within the search period carrying at least one coordinate key term ......................................................................................................................................... 20 Table 2: Common modifiers appearing in patents alongside method and at least one of neural or brain ............................................................................................................................................... 20 Table 3: Common terms describing structures of the brain and numbers of granted patents in which occurrences are exclusive to the terms neural and brain .................................................... 21 Table 4: Common verbs and nouns appearing in patents alongside method and at least one of neural or brain ............................................................................................................................... 22 Table 5: Estimated counts of US patents issued annually for neurotechnology techniques ........ 30 Table 6: Major CPC subclasses assigned to patents issued in neurotechnology techniques ........ 32 Table 7: Bottom-level CPC subgroups specifying treatment contexts ......................................... 34 Table 8: Examples of patents coded to A61N1/36082 or its subgroups for methods of treating cognitive or psychiatric disorders with implantable neuromodulation systems ............................ 35 Table 9: Patents describing neuromodulation techniques directed at cognitive enhancement in healthy populations ........................................................................................................................ 39 Table 10: Prevalence of patents assigned to CPC subgroup A61B5/16 and its child nodes for psychotechnics ............................................................................................................................... 41 Table 11: Descriptions of patents assigned to CPC subgroup G06F2203/011 for emotion or mood input in user-computer interactions ..................................................................................... 43 Table 12: Descriptions of novel applications of machine learning in patents assigned to CPC group G06N20/00 .......................................................................................................................... 44 Table 13: Annual sums of newly granted patents referencing CPC codes associated with non-medical industries .......................................................................................................................... 45 Table 14: Descriptions of neurotechnology patents assigned to CPC subclass G06Q for commerce ....................................................................................................................................... 47 Table 15: Neurotechnology patents coded for ethics concerns .................................................... 50 ix List of Figures Figure 1: The machine that reads minds, the sensational discovery of a German psychiatrist ...... 4 Figure 2: Logic model for patent inclusion and characterization ................................................. 25 Figure 3: Tiers of the Cooperative Patent Classification scheme ................................................. 26 Figure 4: Logic model for evaluating ethics concerns in patents ................................................. 29 Figure 5: Application years of neurotechnology methods patents ............................................... 31 x List of Abbreviations AI Artificial intelligence BCI Brain computer interface BRAIN Brain Research through Advancing Innovative Neurotechnologies CPC Cooperative Patent Classification DARPA Defense Advanced Research Projects Agency DBS Deep brain stimulation DTC Direct-to-consumer EEG Electroencephalography EPO European Patent Office fMRI Functional magnetic resonance imaging iEEG Intracranial electroencephalography IP Intellectual property ML Machine learning R&D Research and development RNS Responsive neurostimulation tACS Transcranial alternating current stimulation TENS Transcutaneous electric neurostimulation tFUS Transcranial focused ultrasound US United States USPTO United States Patent and Trademarks Office VNS Vagus nerve stimulation VR Virtual reality xi Acknowledgements I would first like to acknowledge my supervisor and cheerleader, Dr. Judy Illes, whose insight provided this opportunity and whose compassion sustained me throughout. I am deeply thankful to have a mentor so dedicated to her students and invested in their growth. Without the hearth she created at Neuroethics Canada, this work would have been impossible. To my committee members, Dr. Zelma Kiss and Dr. Paul Pavlidis, thank you for navigating me through the perils of my own curiosity. You elevated my work and tempered my thinking, giving me tools to succeed here and in many projects to come. To the members of Neuroethics Canada and contributors to the International Patent Neuroethics Initiative, thank you for showing me such exceptional enthusiasm and generosity. I owe special debts of gratitude to Marianne Bacani, who saved me countless times over, and Stacey Anderson-Redick, who shared so much of this work with me. To Prof. Dr. Tade Spranger, Dylan Roskams-Edris, Kate Gaudry, and Roland Nadler, thank you as well for your valuable insights. To my family, thank you for inspiring my interest in neuroethics and teaching me to find joy in learning. To my partner, Jessica, your love, warmth, and most of all—patience—have meant the world. Thank you for always believing in me. Finally, I would like to acknowledge the funders who supported this work: the Canadian Institutes for Health Research in partnership with the ERAnet Neuron program, (#ERN-174185/Illes), the Tannenbaum Open Science Institute (#RPB-GR021989/Pavlidis), the National Institutes of Health/National Institute of Mental Health (#1RF1MH117805-01/Illes), the North Family, and the University of British Columbia. xii Dedication To my very first teachers, Dyeda and Saba. . 1 Chapter 1: Introduction On August 6th, 1930, the weekly edition of Düsseldorfer Stadt-Anzeiger ran a public interest article with an unusual headline: Die Machine die Gedanten liest, die sensationelle Entdeckung eines deutschen Psychiaters [The machine that reads minds, the sensational discovery of a German psychiatrist]. The short piece recounted local reporter Walter Finkler’s eyewitness account of an experiment performed by scientists at the University of Jena demonstrating their most recent invention. First, the reporter described the machine: an electrical recording device with long, copper wires leading to silver, needle-shaped electrodes embedded in an assistant’s scalp. A pointer attached to the machine traced rhythmic zigzags onto a paper strip. When the lead investigator, Dr. Hans Berger, offered his assistant a handshake, Finkler recalled how the invention reacted: In the same moment? No, even quicker, a blink of an eye has a snail’s pace compared to the speed of thought. Two-hundredths of a tenth of a second passed between the touch of the handshake and the pointer’s reaction, and in just two-tenths of a second, the feeling was over. The pointer returned to its calm, even, wave-writing (Finkler, 1930). To establish validity, Berger repeated the experiment with different conditions. He poked his assistant with glass rods, then assigned him math problems to solve both in front of the audience and alone in a soundproof room. With each action, pointer’s rhythm changed. More remarkably, repeating an action produced the same rhythm each time. Convinced by the demonstration, Finkler relayed the scientists’ explanation: the oscillating script produced by the machine represented electrical currents generated by the assistant’s brain as by-products of the 2 physical processes underlying his consciousness. With the creation of the elektrenzephelogramme, Berger had tapped into the mechanisms of cognition. Concluding, Finkler looked toward the future: Today they are still secret signs, tomorrow they may perhaps reveal mental and brain illnesses, and the day after tomorrow even letters may be written in brainwriting (Finkler, 1930). Unfortunately, this early piece of speculation left little impact on its audience. By the time other scientists validated Berger’s research, the Second World War was already inevitable, and the ground-breaking achievement that was the electroencephalogram (EEG) was quickly eclipsed (Borck, 2005). Yet, curiosity and vision are far too resilient, and nearly a century later, speculative thinking remains the same: “…technological developments mean that we are on a path to a world in which it will be possible to decode people's mental processes and directly manipulate the brain mechanisms underlying their intentions, emotions and decisions; where individuals could communicate with others simply by thinking; and where powerful computational systems linked directly to people's brains aid their interactions with the world such that their mental and physical abilities are greatly enhanced” (Yuste et al., 2017). Finkler and Yuste share a line of ideation transcending era and expertise. Framed by the broader scope of technical progress, they represent two coordinates on a much larger timeline. In the 1960s, EEG was again recommended as a tool for communication, this time by the United States (US) Air Force (Dewan, 1964, 1966). The 1970s brought attention from computer 3 scientists designing the seminal models of brain computer interface (BCI) (Vidal, 1973). Later, the emergence of biofeedback allowed trained participants to manipulate their neural activity and answer yes-or-no questions with EEG (Elder et al., 1986). Advances in data processing then led to EEG recognition of words (Suppes et al., 1997). Since the creation of EEG-to-speech programs in the late 2000s, the technology has grown sensitive enough to distinguish phonemes across several major languages (Bakhshali et al., 2022; Guenther et al., 2009; Talukdar & Shougrakpam, 2020). As EEG and other neurotechnologies continue to evolve, treatments, life improvements, and even Finkler’s brainwriting will become easier to attain. However, realizing these benefits requires strong moral commitments and consistent decision-making (Garden et al., 2019). With guidance from anticipatory frameworks, different groups can collaborate to promote a widely shared vision. Neuroethicists develop these frameworks to address the social and ethical tensions raised by neurotechnology. With much of today’s innovation fueled by commerce, outreach initiatives increasingly engage with inventors and entrepreneurs (Pfotenhauer et al., 2021). However, these groups are self-selecting. A systematic method of studying the innovation landscape is needed to examine themes in forthcoming commercial neurotechnology. Here, I describe an analysis of patents granted on neurotechnology over a 5-year period to shine light on the contents of recent innovation and support anticipatory neuroethics initiatives with data-driven research. Critically, I do not provide a comprehensive review of innovation in neurotechnology; innovation is far too broad a concept for any single resource to reflect. Instead, I apply methods borrowed from the social sciences and elements of legal scholarship to survey crucial technical features of upcoming neurotechnology products and understand the social and ethical implications of their respective commercial strategies. 4 Figure 1: The machine that reads minds, the sensational discovery of a German psychiatrist (Finkler, 1930). 5 Chapter 2: Background I present a contextual foundation for my thesis work in three sections. In the first, I briefly describe the promise and potential of advanced neurotechnology, both in medicine and society more broadly. In the second section, I introduce the field of neuroethics and summarize its roles in shaping emerging neurotechnology. Last, in the third section I review the value of patent records for research on trends in innovation. 2.1 Neurotechnology With mounting demands straining already tense healthcare systems, developed nations have increasingly searched for solutions using neurointerventions. Statistics Canada reported that in 2017, for example, 22% of Canadians lived with functional disabilities that could possibly be addressed by neurointerventions or other technologies. These conditions are characterized by chronic pain, restricted mobility, seizures, poor mental health, loss of sight or hearing, impaired learning, coordination, or memory, or developmental delay (Cloutier et al., 2018). Despite federal, provincial, and local investments to reduce disease burdens, the far-reaching consequences of pandemic, financial instability, environmental crisis, and demographic change seen in the years since 2017 leave little room for optimistic thought (Berry et al., 2022; Jenkins et al., 2022; Miyah et al., 2022). Critically, Canada is not the only country facing these issues. Neurologic disorders are the leading cause of disability worldwide, afflicting nearly one in three individuals across the course of their lifetime (Feigin et al., 2020; Wijeratne et al., 2022). Neurotechnology describes tools that enable observation of or direct interaction with the living nervous system (Müller & Rotter, 2017). Specifically, neuroimaging allows for study and recording of neural tissue (Bowman, 2014). Neuromodulation, also called neurostimulation, 6 causes changes in patterns of neural activity (Simpson et al., 2022). Neuroimaging and neurostimulation can be combined to provide sophisticated treatment options such as closed-loop responsive neurostimulation (RNS) for epilepsy (Ma & Rao, 2018). In these systems, output from a form of neuroimaging is automatically processed to assign stimulation parameters. Other configurations open further opportunities. For instance, coupling intracranial EEG (iEEG) to a robotic prosthesis may restore mobility and dexterity in patients who have lost voluntary motor function (Iacopi & Lin, 2022). This example constitutes an active brain computer interface (BCI) as the system responds to volitional commands (Mudgal et al., 2020). Alternatively, a system characterized by nociception-sensitive iEEG functionally coupled to an intrathecal pump describes a form of passive BCI. Recent years have marked tremendous increases in international support for translational neuroscience. National research programs such as the Canadian Brain Research Strategy and the United States Brain Research through Advancing Innovative Neurotechnologies (US BRAIN) Initiative, both arms of the International Brain Initiative, and the European Human Brain Project promote far-reaching partnerships and coordinate between one another to achieve complementary aims (Aicardi et al., 2018; Greely et al., 2018; Grillner et al., 2016; Yuste & Bargmann, 2017). Collectively, these sprawling initiatives share two primary objectives: first, to uncover the intricate links between brain and behaviour, and second, to leverage findings in the development of novel neurotechnology (Mott et al., 2018). At the same time, secondary objectives of government agencies, growing buy-in from private firms, and substantial interest from the general public have contributed to and continue to drive proliferation of neurotechnology beyond the boundaries of healthcare (Garden et al., 2019). This has catalyzed 7 dramatic growth in the neurotechnology industry, with extensive participation from big tech companies and the emergence of a rich start-up ecosystem (Saville et al., 2023). Currently, the major spheres of neurotechnology comprise medicine and research, security and warfare, commerce and education, and recreation and enhancement. In medicine and research, applications of neurotechnology are the most diverse, advanced, and widely practiced. Neuroimaging has long been a diagnostic mainstay, providing crucial means of detecting, characterizing, and monitoring intracranial pathologies, among numerous other uses. In the laboratory, these same approaches offer invaluable insights on neurologic phenomena in patients and healthy subjects alike. For example, functional magnetic resonance imaging (fMRI) often drives research paradigms probing the neural correlates of consciousness or psychiatric conditions (Sutterer & Tranel, 2017). Innovation in neuroimaging aims to improve important qualities such as accessibility and performance. Increasingly mobile hardware enables speedier interventions in urgent care settings and opens new opportunities in research on physical activity (Chang et al., 2022; Janssen et al., 2021; Niso et al., 2023). Simultaneously, machine learning (ML) techniques borrowed from the field of artificial intelligence (AI) enable faster, safer, higher quality, and more resource-efficient imaging, pushing diagnostic boundaries in brain tumours, neurologic infections, traumatic brain injury, migraines and facial pain, epilepsy, developmental disorders, and neurodegenerative diseases (Surianarayanan et al., 2023). As for treatment, neuromodulation relieves symptom burden in disorders characterized by motor or autonomic dysfunction (Lai et al., 2019; Rowald et al., 2022), seizures (Simpson et al., 2022), neurodevelopmental delays (Simon et al., 2019), somatic or craniofacial pain (Knotkova et al., 2021), neurodegeneration (Ning et al., 2022), traumatic brain injury (Surendrakumar et al., 2023), and depression (Vlaicu & Bustuchina Vlaicu, 2020). Ongoing 8 areas of research describe additional promise in managing obsessive-compulsive disorder (Borron & Dougherty, 2022), substance use disorders (Lo et al., 2023), psychosis (Martinez-Martin et al., 2018), obesity and eating disorders (da Silva Lira-Batista et al., 2023), and aggressive behaviour (Casula et al., 2023). Innovation in this field pursues safety and accessibility, with advancements in neurosurgery and transcranial modalities such as focused ultrasound dramatically reducing the risks of electrode implantation or open thermoablative procedures in addition to expanding the benefits of neuromodulation to patients previously limited by disability (Asher et al., 2023; Darmani et al., 2022; Schulder et al., 2023). Innovation also pursues efficacy, with adaptive forms of neuromodulation designed with ML techniques supporting sensitive and individualized treatment protocols (Ma & Rao, 2018). Outside of medicine, public and private agencies show shared interest in security and military neurotechnology. Applications in security entail passive BCI configured to identify and authenticate users based on unique patterns of sensed neural activity (Ibrahim, 2022). Use of these services in conjunction with bioauthentication techniques such as iris scans offer significantly heightened protections compared to traditional security protocols and may find use wherever discretionary demands exceed installation and maintenance costs. Military interests in neurotechnology include security but extend far beyond. For example, the US military uses neurofeedback techniques to fortify soldiers’ attentional command and emotional regulation skills ahead of exposure to stressful environments (Smith, 2008). They also use neurofeedback to manage post-traumatic stress disorder (PTSD) resulting from combat (Young, 2018). DARPA (the Defense Advanced Research Projects Agency) funds ongoing efforts in cognitive neuroscience and computer science to develop memory prostheses, enhanced systems for remote communications and mechanical operations, brain-based interrogation tactics, and other 9 logistical and battlefield advantages (Cutsuridis, 2019; Gherman & Zander, 2021; Kosal & Putney, 2023). The China Brain Project shares many of these aims (Kosal & Putney, 2023). In commerce and education, private companies offer both neurotechnology services and products. In the field of neuromarketing, for example, strategic consulting firms use biometric and functional neuroimaging techniques to study consumers’ emotional and cognitive reactions to visual media (Ariely & Berns, 2010). Neuromarketing services are popular among car manufacturers, fashion outlets, food and beverage companies, politicians, and other powerful groups (Hegazy, 2021). In construction and manufacturing, BCI for remote operation of machinery in dangerous or physically demanding tasks may increase productivity and protect labourers from occupational hazards (Gao et al., 2022; Paszkiel, 2022). Some companies market low-cost EEG headsets for real-time analysis of users’ mental states (Alharbi, 2023). These have applications in the workplace and classroom monitoring employees’ and students’ alertness and cognition more broadly (Demir & Demir, 2018; Tindale et al., 2022). In a related branch of industry, a crop of start-ups sells direct-to-consumer (DTC) neuromodulation devices on major online retail platforms, often advertising themselves with unfounded, medicinal claims (Coates McCall et al., 2019; Wexler & Reiner, 2019). At-home uses of neurotechnology typically fall under recreation or enhancement. BCI may support more interactive and immersive forms of digital media, particularly through integration with virtual reality (VR) platforms such as the Meta Quest, which is manufactured by Meta (Kerous et al., 2018). Another domestic area of BCI development focuses on home automation, bridging neurotechnology to smart technology (Das & Saha, 2022). As for enhancement, many social media users active in neurotechnology-focused communities report using transcranial neurostimulation to improve cognitive abilities such as learning and focus 10 (Fisicaro et al., 2020). Neurostimulators used for these practices are often purchased from DTC neuromodulation firms or assembled at home according to online instructions (Wexler, 2020) Less than a century has elapsed since the invention of EEG, and already the distance in technical capacity is immense. Neurotechnology innovation will continue, and the diversity in neurotechnology seen today is no more than a preview of the decades to come. Major funding initiatives such as the US BRAIN Initiative and others underscore this promise and view. However, these new opportunities will come with new risks. To ensure individual and societal wellbeing, responsible practices are needed. 2.2 Neuroethics and Responsible Innovation By providing access to the active brain, neurotechnology renders processes of the mind such as intention, learning, and arousal both visible and mutable (Rose & Abi-Rached, 2014). While necessary to achieve its beneficial aims, the ability to observe and interfere with these processes also raises important tensions with human rights (Farah, 2012). These concerns fall within the domain of neuroethics, a field of scholarship concerned with the ethical, legal, and social implications arising from an expanding neuroscience (Farah, 2004; Illes et al., 2003). Recent efforts to build inroads into the innovative front of neurotechnology have resulted in ethics frameworks outlining value-driven decision-making across the product development timeline (Pfotenhauer et al., 2021). Even as current partners adopt these frameworks, however, methods of monitoring the neurotechnology landscape and identify emerging actors, products, and technical trends are still evolving. Human rights are the collection of entitlements assigned to a person purely on the basis of their being human (Dembour, 2010). In practice, they stabilize vastly complex and 11 interconnected societies by creating normative institutions for behavioural governance (Stammers, 1999). The United Nations delineates basic human rights in the "Universal Declaration of Human Rights" (1948), identifying rights to freedom, equality, privacy, personal security, and freedom of thought, among others. Many nations around the world reaffirm their commitments to human rights with statutes extending parallel liberties to their citizenry. For example, Canadian rights to freedom, equality, privacy, personal security, and freedom of thought are also protected by the "Canadian Charter of Rights and Freedom" (1982). Neurotechnology raises unique human rights concerns by allowing inference to and in some cases interference in mental processes. In doing so, they undermine historical views of the mind as an “unassailable fortress” or “the last refuge of personal freedom and self-determination,” opening new opportunities for intrusion, manipulation, and exploitation (Ienca & Andorno, 2017). Harmful consequences of neurotechnology betray the intentions of the neuroscience community and detract directly from the promise of the field. Therefore, wherever neurotechnology goes, a need for guidance on responsible practices will follow. Neuroethicists answer this call, drawing on a variety of methods to foreground these concerns and engaging with stakeholders to embed social, ethical, and legal analyses within broader sociocultural contexts (Northoff, 2009; Sullivan & Illes, 2017). Prominent voices in neuroethics argue that the best way to address the risks posed by neurotechnology is through widespread adoption of four additional human rights (Baselga-Garriga et al., 2022). These so-called neurorights include rights to cognitive liberty, mental privacy, mental integrity, and psychological continuity (Ienca & Andorno, 2017). Cognitive liberty is the most fundamental of the four, guaranteeing rights to alter one’s own mind with 12 neurotechnology as well as rights to refuse (Bublitz, 2013) . Mental privacy subsequently places safeguards around neurologic data, particularly forms from which mental insights may be drawn (Ienca & Andorno, 2017). The proposed right to mental integrity ensures access to psychiatric care and safeguards against malicious brain-hacking and memory interference (Ienca & Haselager, 2016). Last, psychological continuity entails protections against actions resulting in unconsented personality changes (Ienca & Andorno, 2017). Ienca and Andorno note that the latter three neurorights are relative and may be superseded by utilitarian ethics in cases such as criminal rehabilitation. Some have criticized neurorights as an unnecessary exercise in rights inflation, arguing that current doctrine may already address these concerns (Bublitz, 2022). These voices encourage the expanded interpretations of existing codes over the addition of new and untested language to statutes. Many parallel neuroethics initiatives focus on engaging policymakers and innovators to identify and restrict uses of neurotechnology violating human, civil, and labour rights, develop schemes to safeguard data representing neural activity, and create procedures for responding to future issues (Ebert et al., 2021; Minielly et al., 2020). Collaborations with technology developers have so far proven fruitful (Bowman et al., 2018). Innovators often express preferences for proactive measures supporting responsible design and data stewardship (Pfotenhauer et al., 2021). Ethical guidance in these areas benefits not only end-users who enjoy a secure and reliable service but also neurotechnology firms that build public trust by demonstrating commitments to social responsibility (Bowman et al., 2018). Neuroethicists encourage neurotechnology firms to adopt user-centered design frameworks, wherein diverse end-user perspectives are incorporated into the innovative process itself (Stahl et al., 2021). 13 Theoretically, these frameworks output higher quality products, which are accessible to broader audiences. The mobilization of neurotechnology stakeholders by neuroethicists and bottom-up integration of ethical values in practice, governance, and design represents a historic achievement. However, it is not a complete solution. Far from uniform, neurotechnology innovation is diverse in terms of form, application, sophistication, and regulation (Higgins et al., 2022). Advances spread rapidly, draw from different fields, and are subject to evolving governance requirements. To promote rapid and effective innovation, neuroethicists propose frameworks that unite the upstream elements of responsible design with the downstream and context-specific elements introduced by different cultures, regulatory bodies, and market conditions (Garden et al., 2019). For example, the meticulous transparency framework requires developers to publicly share and explain the rationale, methods, and potential consequences of their project (Benrimoh et al., 2018). Though a helpful conceptual aid, this framework becomes impractical once development commences. Alternatively, the AIM framework counsels a future-facing approach grounded in inclusivity, integrity, and communication (Garden et al., 2019). “A” stands for anticipate and articulate, requiring innovators to predefine their values and goals, embrace stakeholder voices, and share knowledge gained through dissemination of successful and unsuccessful products alike. “I” is for implement and integrate. This aspect calls for innovators to establish and adhere to ethical benchmarks, thereby promoting planning and limiting unethical abandonment of active clinical trials. The “M” calls on others to monitor and measure for ethical reproducibility in all experimentation. With historical precedent cautioning strongly against industrial self-regulation, “M” applies not only to innovators developing their products but also charges stakeholders and other neuroethicists with scrutinizing practices across 14 the neurotechnology innovation landscape. By studying trends in the landscape, neuroethicists may better understand priorities in innovation, outline novel concerns, and deliberate data-driven recommendations for responsible development. 2.3 The Patent Landscape Patent authorities encourage inventors to publicly disclose their achievements by awarding them exclusive commercial privileges over the contents of their disclosures. Privileges may last up to 20 years and, while active, grant their holders rights to exclude any other commercial operator from advertising, manufacturing, or utilizing their invention (CIPO, 2021). In exchange, the public may freely study the invention, and upon the expiry of a patent, all may also replicate it commercially. This quid pro quo agreement, wherein the public exchanges a limited range of their rights to grow the seeds of innovation, reflects the utilitarian assumption underpinning all patent regimes: patents increase innovation; innovation promotes economic growth and public welfare (Devlin & Sukhatme, 2009). Analyses of the patent landscape are used to: (a) assess the novelty of an invention, (b) study trends in inventions, (c) predict trajectories of technologic development, (d) plan investments, (e) identify infringing technologies, (f) evaluate qualities of inventions, (g) find potential competitors or partners, (h) determine technologic vacuums or hotspots, and (i) outline evolving commercial strategies (Abbas et al., 2014; Choi & Hwang, 2014; Jeong & Kim, 2014). To date, very few analyses have examined the neurotechnology landscape per se. One industry report provided by Clarivate, an analytics firm, identifies 16,723 relevant applications filed with ten prominent patent authorities between 2008 and 2016, representing an overall increase in applications of 154% in that time (Garden et al., 2019). The authors divide patents across six 15 technologic categories: neuromodulation (N=10,375), neuroprosthetics (N=7,432), neuroimaging (N=1,854), neurosensing (N=1,768), neurorehabilitation (N=1,094), and BCI (N=574). The bulk filed were in the US. For the same period, a second analytics firm called NTX Services counts 57,622 filings across all authorities in the same period, corresponding to a 222% increase in applications (2022). Again, most filings are in the US. Together, these reports indicate rapid commercial escalation focused on neuromodulation technologies within US-based markets. However, the methodologies leading to these conclusions are unpublished, preventing external validation. Nonetheless, other analysts agree that neurotechnology is growing overall, with neuromodulation accelerating especially rapidly. Marcus et al. (2015) describes trends in neurosurgical patents issued by 90 different authorities in the five decades spanning 1960 to 2010. Using a simple text-mining approach based on the keyword neurosurgery, they identify 11,672 relevant patents issued in this period. Image-guidance made up the largest technologic cluster, encompassing 2,625 patents or 38% of the total population. Neuromodulation, however, made up the fastest growing cluster, representing 1,294 patents or 19% of the surveyed set. Moreover, 40% of neuromodulation patents (N=517/1,294) were granted in the final five years examined. Assuming sustained growth, these data indicate international innovation in neuromodulation technology outpaced neuroimaging around the year 2010. The same study also finds deep brain stimulation (DBS) to be the dominant form of neuromodulation, representing 22 of the 33 most financially successful neurotechnology patents. Spinal cord stimulation followed with 6 of 33, peripheral nerve stimulation with 2, and combinations of these functions with 4. These figures may explain two of the technologic categories reported by Clarivate. As DBS fulfills criteria for both neuromodulation and neuroprosthetics, the abundance of patents recorded 16 in both categories may reflect a core industrial emphasis on DBS development. Crucially, spinal cord stimulation and peripheral nerve stimulation may also meet criteria for both categories and contribute to their high counts. Further study of the more recent landscape is needed to disentangle these trends. Narrower analyses of innovation landscapes describe trends within fields, elucidating how specific technologies may evolve over time. Greenberg et al. (2021) presented their research on global patent activity in the field of BCI that occurred between 1980 and 2020. By combining text-mining and class-evaluation selection methods, the authors identified 2,161 patent applications, 510 of which were filed in 2020 alone. Here, rapid growth in BCI patent activity appears to align with that previously seen in neuromodulation inventions. Furthermore, 77% of the applications were active or pending at the time of data collection, indicating strong intentions among applicants to further refine their inventions into commercial goods. Considering the powerful deterrent of multi-year application backlogs, low abandonment among applicants may attest to their optimistic expectations of the field (Zhang et al., 2017). As with Clarivate and NTX Services, Greenberg et al. (2021) place the US at the center of innovation, with the USPTO receiving 47% of all applications surveyed. By studying the number of patents in which specific keywords appeared, they also revealed important insights on BCI innovation. The term treatment occurred in the specifications, or body, of 53% of applications, diagnose in 34%, and rehabilitation in 26%. According to Greenberg et al., this represents a core industrial emphasis on clinical BCI. Another perspective of the neurotechnology innovation landscape examines a class of patents rather than technologies. Medical methods patents grant proprietary rights over clinical 17 procedures (Kubick, 2010). They are banned in over 80 countries worldwide for undermining public welfare and restricting doctors’ judgement (Mitnovetski & Nicol, 2004). Only the USA and Australia grant them (Gold et al., 2010). Given the leading role of the USA in disseminating innovations via patents, study of its medical methods patent landscape may reveal otherwise unrecorded trends and advancements in clinical and dual use neurotechnology. Furthermore, the contents of these patents may have key implications for researchers who are not protected from infringement suits as well as doctors whose statutory protections have yet to be tested by the courts (Mueller, 2004). Previously, Roskams-Edris et al. (2017) found evidence of a vast increase in the annual counts of patents granted in the 20 year period prior to 2015 for medical methods that target neural structures. Though this research focused on claim breadth, the data still support a perspective of medical methods patents as untapped resources of information about critical trends in neurotechnology innovation. 2.4 The Neuroethics Challenge Progress in neurotechnology opens new doors to both benefits and harms. As the state-of-the-art changes, responsible innovation will attenuate risks. My goal is to study the patent record and deliver a systematic method of examining trends in innovation, thereby closing blind spots the neurotechnology landscape. 18 Chapter 3: Research Methods Using qualitative and quantitative methods, I will address the following specific research questions: 1. What are the technical trends within the neurotechnology innovation landscape in the five years spanning 2016-2020? 2. What are the ethical and social implications arising from the trends on this neurotechnology innovation landscape? These questions derive from and build upon prior work conducted by and published in Roskams-Edris et al. (2017). I was specifically interested in the technical trends and broader ethical implications associated with a 14-fold increase in neuromodulation methods patents between 1995 and 2015. I focused on the 5-year period following that body of work. To this end, I first detail the process of database creation for which I developed and applied a structured search algorithm for patent collection. Next, I discuss designing and applying a semi-structured questionnaire to guide my content review. I conclude this chapter by outlining my procedures for the ethical analysis of patented neurotechnology techniques. 3.1 Creation of the Database I applied the methodologies primarily outlined in Roskams-Edris et al. (2019; 2017) and Illes et al. (2019) to the data identification and compilation steps of the research. First, I developed a structured search algorithm utilizing an approach based in text-mining. Text-mining search techniques utilize structured algorithms to collect patents meeting customized lexical 19 criteria (Clarke, 2018). However, obstacles such as polysemes, synonyms, and intentionally obscure language may prevent complete coverage within a given field (Noh et al., 2015). To maximize coverage, I adapted the algorithm used by Roskams-Edris et al. to target patents with common, neurotechnology-associated key terms. I approached this by finding the broadest possible range of potentially relevant patents and narrowing the scope with key terms from the initial algorithm appearing in 5% or more of results. I also obtained and studied the prevalence of all synonyms of key terms listed on Thesaurus.com (Clarke, 2018). I then arranged like key terms in a series of word banks, which were finalized with my in-house mentors and experts in neuroethics, neurosurgery, and neurology within the lexicons of their respective fields. My mentors also provided a bank of neuroanatomical keywords to direct the search algorithm at patent claims referencing specific brain structures. The final set of key words was determined by unanimous agreement of the research team. All searches were performed on Lens.org. Neural and brain were the two most common anatomical terms identified in the patent record. Uniting the terms with an inclusive disjunction yielded the broadest possible range of results, totalling 48,119 patents. 20 Neural Brain Spinal Spine Nerve Neuron Neural 26,372 48,119* 41,739 41,190 37,566 30,338 Brain 48,119* 23,421 36,521 38,214 33,998 28,799 Spinal 41,739 36,521 15,784 28,310 26,668 21,711 Spine 41,190 38,214 28,310 14,976 27,233 21,635 Nerve 37,566 33,998 26,668 27,233 12,663 18,636 Neuron 30,338 28,799 21,711 21,635 18,636 6,691 Table 1: Numbers of patents granted within the search period carrying at least one coordinate key term (N = A and/or B). Italicized figures represent a single key term. Asterisks (*) denote maximum values within the set. Appending the key term method ([neural and/or brain] and method) reduced the total number to 37,909 relevant patents. Semantic operators that commonly modify or are modified by the key anatomical terms of Table 1 were then identified. Six (6) co-occurred with method and at least one of neural or brain in wide swaths of the landscape (N ³ 37,909 × 5%): tissue, location, region, area, site and deep (Table 2). No secondary meanings were identified for key term pairings. Key Terms Patents (N) Co-occurrence (%) Tissue 6,365 17 Location 5,041 13 Region 4,576 12 Area 4,314 11 Site 2,918 8 Deep 2,443 6 Table 2: Common modifiers appearing in patents alongside method and at least one of neural or brain. Twenty-nine (29) terms occurring exclusively from neural or brain in fewer than 1,000 granted patents were selected (Table 3). 21 Key Terms Exclusive Occurrences (N) Cortical 951 Occipital 446 Dentate 259 Sulcus 253 Parietal 223 Cerebellum 89 Hippocampus 80 Basal Ganglia 78 Cerebral Cortex 40 Thalamus 40 Cingulate 37 Amygdala 29 Putamen 25 Substantia Nigra 21 Caudate 21 Accumbens 20 Midbrain 18 Periventricular 14 Subthalamic 13 Forebrain 13 Gyrus 13 Globus Pallidus 11 Subgenual 10 Brodmann 9 Cingulum 7 Internal Capsule 6 Habenula 6 Pedunculopontine 2 Subcallosal 1 Table 3: Common terms describing structures of the brain and numbers of granted patents in which occurrences are exclusive to the terms neural and brain. Fourteen (14) key verbs and nouns co-occurred with method and one or both of neural and brain in broad swaths of the landscape (N ³ 37,909 × 5%). Within the context of neurotechnology, selected terms described clinical, physiological, or technical operations, and combinations with other key terms revealed no associations with other industries. 22 Key Terms Patents (N) Co-Occurrence (%) Cause 13,359 35 Device 12,229 32 Treat 10,842 29 Inhibit 6,645 18 Image 6,142 16 Stimulate 5,743 15 Activate 5,539 15 Adjust 5,320 14 Support 3,615 10 Interface 3,352 9 Electrode 2,727 7 Modulate 2,692 7 Diagnose 2,547 7 Record 2,472 7 Implant 2,406 6 Enhance 2,036 5 Table 4: Common verbs and nouns appearing in patents alongside method and at least one of neural or brain. Logical operators were inserted such that the structured search algorithm would identify all granted patents with claims containing the term method, if not neural or brain and a key term from each of Tables 2, 3, and 4. The following algorithm resulted: Claim:(method) AND ((claim:(brain OR neural) AND claim:(area OR deep OR location OR region OR site OR tissue)) OR (claim:(accumbens OR amygdala OR basal ganglia OR Brodmann OR caudate OR cerebellum OR cerebral cortex OR cingulate OR cingulum OR cortical OR dentate OR forebrain OR globus pallidus OR gyrus OR habenula OR hippocampus OR internal capsule OR midbrain OR occipital OR parietal OR pedunculopontine OR periventricular OR putamen OR subcallosal OR subgenual OR substantia nigra OR subthalamic OR sulcus OR thalamus))) AND claim:(activate OR adjust OR cause OR device OR diagnose OR electrode OR enhance OR image OR implant OR inhibit OR interface OR modulate OR record OR stimulate OR support OR treat) I applied the algorithm and filters to Lens.org, an online, open-access, patent repository. The algorithm queried all patents issued by the USPTO in the five years spanning January 1, 2016, to December 31, 2020, and returned the set meeting its criteria. Data collection occurred 23 on September 20, 2021. I exported my collection to Microsoft® Excel® for Microsoft 365 MSO (Version 2210 Build 16.0.15726.20070) 64-bit, a UBC-licensed spreadsheet software program, for further analysis. Exported data included titles, hyperlinks, owners, applicants, inventors, issuing jurisdictions, classifications, dates of application and publication, priority numbers, platform-assigned identification codes, and family sizes. 3.2 Guided Review Through an iterative and collaborative process, I created a semi-structured questionnaire in Microsoft® Excel® for Microsoft 365 MSO (Version 2210 Build 16.0.15726.20070, 64-bit) to facilitate standardized patent review. The questionnaire opened with criteria asserting an a priori definition of brain-related methods patents. All other nodes were generated through the following steps: (1) I independently applied these criteria to a random sample of 20 patents in the downloaded database and maintained field notes on unaddressed and emergent characteristics informative to the aims of the study. (2) After completing each sample, I met with other members of the research team to compare field notes and refine the questionnaire. Upon reaching consensus, I generated another random sample of 20 patents with which to test the improved questionnaire. (3) I repeated this process until all characteristics relevant to neurotechnology were fully addressed. After finalizing the questionnaire, another researcher (R2) and I (R1) independently applied it to a random sample of the patent database. I assessed interrater reliability in the sample 24 using Cohen’s Kappa and proceeded to extend the analysis when high coding reproducibility (k>0.80) was confirmed (Bakeman et al., 1997). The resulting analytical model consisted of eight steps (Fig. 2). Steps 1 and 2 provided inclusion criteria. Specifically, I examined the claims of each patent and included only those possessing independent methods claims describing interactions with the human nervous system or its functions. The next five steps focused on the essential, innovative qualities of each invention. Through Steps 3 and 4, I identified and documented any aspects of neuromodulation, such as when energy applied to the nervous system alters the structure or activity of a region of interest. Similarly, in Steps 5 and 6, I highlighted techniques involving neuroimaging or downstream applications of brain-based data. In Step 7, I summarized the innovative nature of the disclosed technique regarding its prior art, emphasizing its practical applications. Step 8 called for critical reflection. Here, I committed my interpretation of the invention to the record as field notes, logged important features such as cognitive enhancement or emotion detection, and designated the patent for further discussion with other research team members as necessary. 25 Figure 2: Logic model for patent inclusion and characterization. After manually curating the database, I obtained a complete list of unique cooperative patent classification (CPC) subgroup designations from the patents that remained. As shown in Figure 3, CPC is a 5-tiered coding hierarchy used by the United States Patent and Trademark Office (USPTO) and European Patent Office (EPO) to index critical technical features in patents (Montecchi et al., 2013). Over 250,000 subgroups act as bottom-level, mutually non-exclusive 26 indicators of precise mechanical and operational details. Subgroups are assigned by patent examiners in the application process, and agencies regularly publish revisions to better reflect the ever-evolving innovation landscape (Tran & Kavuluru, 2017). Figure 3: Tiers of the Cooperative Patent Classification scheme (CPC) with example provided. With subgroup codes as column headers, I constructed a data validation table to ascertain the relative prevalence of different bottom-level technical themes (Al Hariri, 2023; Alharbi, 2023; Lochmiller, 2021; Thomas & Harden, 2008). I retrieved definitions of and hierarchical relationships between classifications from the official website of the issuing agency (uspto.gov/web/patents/classification). I also excluded references to retired classifications. I focused on classification prominence in subject matter related to neuromodulation and neuroimaging. I additionally examined classifications associated with important fields outside of medicine, such as AI and commerce. 27 3.3 Patent Characterization I developed and implemented an analytical model promoting structured identification and evaluation of ethical issues raised by patented techniques (Fig. 4). The model adopted a deductive, neuroethical approach wherein fundamental moral principles extensively characterized by neurorights frameworks—namely freedoms of thought, privacy, mental integrity, and personal identity—were applied in a top-down analysis of the real-world applications of novel neurotechnology techniques as described by their specifications (Farisco et al., 2022; Ienca, 2021; Inglese & Lavazza, 2021; Yuste et al., 2017). I selected a fifth principle—scientific validity—to identify unsubstantiated and potentially harmful services or treatments (Eijkholt, 2020). Additionally, I engaged five independent reviewers to achieve a rigorous and multidisciplinary perspective of emergent tensions. In the first step of the model, R2 and I (R1) independently conducted principled reviews of the neurotechnologies as outlined in their disclosures and recorded tensions emerging from their widespread use. For instance, proposals to use EEG to monitor feelings of role fulfillment among employees in an office environment may raise privacy concerns (Tindale et al., 2022). R2 and I deduced potential uses of neurotechnologies from a literal reading of their claims. Borrowing from the patent litigator’s toolbox, we based our interpretations in the exemplary uses outlined as preferred embodiments (Brody, 2009). Preferred embodiments highlight specific ways in which a patented technology may be used once fully matured. I compiled our results afterward, retaining only the patents identified by at least one reviewer. Following compilation, I engaged additional reviewers in a high-level assessment of moral significance and validity. I began by sharing identified patents and brief descriptions of 28 corresponding ethical, legal, and social tensions with four reviewers—R2, R3, R4, and myself—to independently evaluate the magnitude of concern associated with each. Evaluations were assigned on a 5-point scale (1: low; 5: high) and based in holistic appraisals of the likelihoods and severities of benefits and harms linked to potential uses. In the next step of the model, I collected evaluations and excluded from further review all patents with average rating of less than four (<4). I then provided the patents coded as high concern (4 and 5 on the scale) to a fifth reviewer with subject expertise (R5) for independent validation. Validated patents were probed further for the a priori themes of freedoms of thought, privacy, mental integrity, personal identity, and scientific validity, as well as those emerging, and are reported. For patents linked to concerns for scientific validity, I used backward citations to non-patent literature as an indicator of technical merit (Hirschey & Richardson, 2004; Narin & Hamilton, 1996). 29 Figure 4: Logic model for evaluating ethics concerns in patents. 30 Chapter 4: Results In this chapter, I detail the results of the research. First, I examine the components and outcomes of my structured search algorithm. Next, I describe trends in the neurotechnology patent landscape. Finally, I highlight exemplary patents intersecting with critical themes in ethical innovation. 4.1 Patent Search Application of my algorithm to Lens.org yielded 3,065 patents issued by the USPTO and EPO between January 1, 2016, and December 31, 2020. USPTO patents accounting for 89% of the collection (N=2,737) were retained for characterization. Cohen's Kappa coefficient (k) calculated for a random sample of N=100 patents was 0.97, indicating a high degree of interrater reliability when applying the model to collected patents. Application of the logic model to the entire dataset identified N=779 patents, or 28% of the initial database meeting inclusion criteria (Table 5). Year Granted Patents (N) 2016 137 2017 155 2018 141 2019 165 2020 181 Total 779 Table 5: Estimated counts of US patents issued annually describing neurotechnology methods. Application years of collected patents ranged from 2003 to 2019 (Fig. 5). Approximately 50% (N=393/779) of patents granted between 2016 and 2020 stemmed from applications filed 31 between 2014 and 2016. Applications for 42% (N=331) were filed in or after 2016. An average of 3 years elapsed between dates of application and issuance. Figure 5: Application years of neurotechnology methods patents. 4.2 Landscape Characterization CPC code extraction yielded 9,111 references spanning 1,983 unique, bottom-level subgroups. Eight (8) major subclasses emerged through hierarchical analysis (Table 6). The most prevalent subclass is A61N, which designates different forms of neurostimulation, neuromodulation, electrotherapy, and magnetic therapy. It applies to 73% (N=571/779) of patents and accounts for 36% (N=3,309/9,111) of references. A61B is the next major subclass, signifying innovation in the fields of diagnostics, surgery, and bio-authentication, and including many applications of EEG and neuroimaging. CPC subgroups descended from A61B are attached to 55% (N=426/779) of patents and represent 36% (N=3,284/9,111) of references. The G16H subclass provides 16% (N=121/779) of patents and 3% of references (N=282/9,111). G16H identifies healthcare information and communications technology (ICT) such as computer-aided diagnoses, disease modeling, and medical report generation. The fourth major 05010015020020032004200520062007200820092010201120122013201420152016201720182019Applications Submitted (N)Year 32 subclass, A61M, specifies medical devices for drug delivery, respiratory support, wound care, dialysis, infusion, and various other medical treatments. It supplies 11% (N=87/779) of patents and 5% (N=472/9,111) of references, primarily indicating infusion pumps and probes. The remaining subclasses each represent less that 10% of the data. Subclass Abbreviated Description Frequency (%) Patents (N) A61N Therapeutic energy applications 73 571 A61B Diagnostics and monitoring 55 426 G16H Healthcare informatics 16 121 A61M Treatment apparatus 11 87 A61F Surgical devices and prostheses 8 63 G06T Image generation and processing 6 49 G01R Electromagnetic measurement and testing 6 48 G06F Digital data processing 5 40 Table 6: Major CPC subclasses assigned to patents issued in neurotechnology techniques. Four (N=4) groups within the A61N subclass categorize novel neuromodulation techniques by form of energy. The sample is dominated by electrotherapy methods such as DBS and transcutaneous electrical nerve stimulation (TENS), with corresponding group code A61N1 seen in 64% (N=499/779) of patents. In contrast, only 10% (N=78) of patents pertain to magnetic therapies, as indicated by group code A61N2. Nine percent (9%, N=72) of patents are coded to A61N5 and provide methods of radiation therapy, most often detailing advances in optical stimulation. Ultrasound therapy is the least prevalent group category, with A61N7 attached to 5% (N=39) of patents. Two (N=2) high-level subgroups within the A61N1 hierarchy distinguish novel methods of neurostimulation performed with implantable pulse generators (IPGs) from those performed 33 with external stimulators. Of patents examined, 47% (N=375/779) imply or encompass surgical implantation procedures, as indicated by subgroup A61N1/3605 or one of its child nodes. In comparison, 25% (N=196) of patents list A61N1/36014 or an associated child node, protecting in their disclosures transcranial and transcutaneous techniques. Notably, 12% of patents (N=92) reference child nodes of both high-level subgroups. Twenty (N=20) bottom-level subgroups additionally describe the health conditions targeted by neurotechnology treatments: 17 descend from A61N1/3605 and 3 from A61N1/36014 (Table 7). Data validation determined 6 major subgroups, the largest of which—A61N1/36082—corresponds to 14% (N=112/799) of patents and addresses implantable neuromodulation treatments for cognitive and psychiatric disorders such as dementia and major depressive disorder. References to A61N1/36082 overlap with A61N1/36096 in N=18 patents, A61N1/36092 in N=9, A61N1/36085 in N=1, and A61N1/36089 in N=2. The second and third most prevalent subgroups also involve neuroprostheses: A61N1/36071, found in 12% (N=96) of patents, signalled analgesia, while A61N1/36067, also seen in 12% (N=91) of patents, classifies interventions for improving motor control. A61N1/36071 and A61N1/36082 co-occur in N=19 patents, while A61N1/36067 and A61N1/36082 co-occur in N=53. 34 Subgroup Target condition or process Frequency (%) Patents (N) A61N1/36082 Cognitive or psychiatric disorders [sic] 14 112 A61N1/36071 Pain 12 96 A61N1/36067 Movement disorders 12 91 A61N1/36025* Mental or cerebral conditions [sic] 9 74 A61N1/36064 Seizures 6 49 A61N1/36021* Pain 5 36 A61N1/36114 Cardiac control 4 30 A61N1/36103 Neurorehabilitation 3 27 A61N1/36117 Hypertension 3 27 A61N1/36096 Mood disorders 3 26 A61N1/361 Phantom sensations 1 10 A61N1/36078 Sleep or relaxation 1 9 A61N1/36092 Mental training 1 9 A61N1/3611 Respiration control 1 9 A61N1/36075 Headache or migraine 1 8 A61N1/36085 Eating disorders or obesity 1 7 A61N1/36107 Sexual dysfunction 1 7 A61N1/36121 Neurotransmitter production 1 7 A61N1/36089 Addiction or withdrawal 1 4 A61N1/36028* Aversion therapy 0 0 Table 7: Bottom-level CPC subgroups specifying treatment contexts. Asterisks (*) indicate classifications for non-invasive treatments. Descriptions of target conditions and processes were retrieved directly from uspto.gov/web/patents/classification. 35 Thirty-seven (N=37) patents coded to A61N1/36082 or a corresponding child node propose treatments for psychiatric conditions involving cortical or subcortical neuroprostheses. I detail five exemplary treatments in the following paragraphs (Table 8). US Patent No. Title Owner Brief Description 9,248,280 Closed-loop feedback for steering stimulation energy within tissue Boston Scientific Neuromodulation Corp. Adjusting intracranial neuromodulation in response to sensed patient desires. 9,345,880 Closed-loop feedback-driven sympathetic neuromodulation for affect control Dilorenzo Biomedical LLC Delivering intracranial neuromodulation in response to sensed mood disturbances. 9,700,715 Lead, device, and method for electrical stimulation of deep brain Sceneray Co. Ltd. Delivering DBS to treat substance use disorders. 10,413,235 Hybrid system for treating mental and emotional disorders with responsive brain stimulation General Hospital Corp., Massachusetts Institute of Technology, Univ. of Washington Delivering intracranial neuromodulation in response to volitional neural commands. 10,688,303 Therapy target selection for psychiatric disorder therapy Medtronic Inc. Detecting and modulating patient mood with DBS to reduce psychiatric symptoms. Table 8: Examples of patents coded to A61N1/36082 or its subgroups for methods of treating cognitive or psychiatric disorders with implantable neuromodulation systems. US No, 9,248,280 (the ‘280 patent) represents an early foray into RNS by Boston Scientific Neuromodulation, a subsidiary of medical engineering titan Boston Scientific. With an initial application submitted in 2007, the patent claims a method of adjusting stimulation in an 36 intracranial implant to treat limbic disorders among other forms of neurologic dysfunction (Moffitt et al., 2016). Specifically, it discloses a novel adjustment mechanism. The device automatically “displace[s] the locus of stimulation” in response to a “cognitive brain signal… obtained from a brain region that can be correlated to intentions of the patient” (Moffitt et al., 2016). US No. 9,345,880 originates from an application first submitted in 2006. Created by an American neurosurgeon and assigned to a company under his name, the patent discloses an intracranial implant and method of treatment delivery. In this case, a sensing module and signal processor identifies “a neural state which is related to at least one sign or symptom… of depression, bipolar disorder, and [or] mania” (Dilorenzo, 2016). Consequent stimulation delivered by a control module would alter activity of the frontal cortex, thalamus, basal ganglia, limbic system, or autonomic nervous system, ultimately “caus[ing] affect to remain within a desired range.” US Patent No. 9,700,715 is owned by Sceneray, a neuromodulation development firm based in Suzhou, China. It corresponds to an application first submitted to Chinese patent authorities in 2014, then re-submitted to the USPTO. In the brief document—only 9 pages with diagrams—the inventor outlines a DBS technique targeting “the nucleus accumbens and anterior limb of an internal capsule… for treating drug addiction” (Dou, 2017). Just one other patent proposed DBS in the context of addiction treatment: under co-ownership of the King Saud University, King Abdullah International Medical Research Center, and the Kingdom of Saudi Arabia Ministry of National Guard Health Affairs, US Patent No. 10,780,264, protects a DBS system and its therapeutic applications, including but not limited to managing symptoms of substance withdrawal (Alam, 2020). 37 As with the ‘280 patent, US No. 10,413,235 claims to “provid[e] the patient intentional control over the applied stimulation” delivered by closed-loop, DBS treatment for psychiatric disorders (Widge et al., 2019). Dated to an application submitted in 2015, the inventors ground their disclosure in their prior research on neuroplasticity observed in rodents learning to control BCI (Widge et al., 2014). They propose that, in the same manner, patients with psychiatric conditions who are aware of their altered states could learn to use an appropriately programmed DBS unit to dynamically suppress ego-dystonic symptoms. US Patent No. 10,688,303 began as an application submitted in 2008 by Medtronic, the world’s largest medical device company (Lenzer, 2018). It provides a distinct approach to intracranial neuromodulation treatment for psychiatric disorders, wherein a processor first evaluates the severity and duration of a symptom comprising “fatigue, anhedonia, depressed mood, loss of energy, insomnia or hypersomnia, and the second patient symptom comprises at least one of decreased need for sleep, distractibility, psychomotor agitation, irritable mode [sic] or inflated self-esteem” (Rise & Giftakis, 2020). Upon determining a patient’s symptom or mood state, the device automatically delivers electrical energy to the appropriate tissue, thereby treating the disorder. Seven percent (7%, N=51/779) of patents protect neuromodulation techniques for improving cognitive processes. They span the CPC subgroups of A61N1/36082 for cognitive or psychiatric treatments, A61N1/36025 for non-invasive mental or cerebral treatments, and A61N1/0456 for TENS. Most describe enhancement solely in the context of treatment, facilitating cognitive skills affected by neurodegenerative diseases, brain injury, or developmental conditions. Only N=5 patents distributed across three companies propose cognitive enhancement for healthy populations (Table 9). Each was granted in 2020. Two (N=2) 38 describe methods of enhancing learning capabilities by delivering either TENS or transcranial alternating current stimulation (tACS) to the cranial nerves during skill rehearsal (Goodall et al., 2020a, 2020b). Their owner, Elwha, shares an address with Intellectual Ventures, the world’s largest non-practicing entity, or patent troll (Carrier, 2015; Detkin, 2006; Rimmer, 2018). Both terms refer to companies with business models centered around acquiring patents and charging others licensing fees for access. Crucially, these companies do not themselves attempt to develop new technologies based on the patents they obtain. Thus, their role in the innovation ecosystem is often characterized as parasitic (Seidenberg, 2006; Teska, 2011). The remaining N=3 patents pertaining to cognitive enhancement belong to private research and development (R&D) firms funded by the DARPA Returning Active Memory Replay Project (Howard & Pilly, 2020; Mohammadrezazadeh et al., 2020; Simons et al., 2020). Each discloses a method of enhancing memory consolidation with transcranial stimulation delivered during skill rehearsal, just following practice, or during quiet sleep. 39 US Patent No. Title Owner Brief Description 10,596,372 Targeted steerable transcranial intervention to accelerate memory consolidation HRL Laboratories Inc. Delivering tACS while practicing a skill or asleep to support memory encoding. 10,660,569 Apparatus, system, and methods for targeted memory enhancement during sleep Teledyne Scientific & Imaging LLC Combining EEG and transcranial stimulation during sleep to sense and evoke memory biomarkers. 10,695,570 Prompting system and method for enhancing learning with neural modulation Elwha LLC Delivering TENS to cranial nerves while practicing a skill to promote uptake. 10,736,564 System and method for enhancing learning of a motor task Elwha LLC Delivering TENS to cranial nerves while rehearsing a complex motor skill to promote uptake. 10,835,176 Personalized closed-loop pulsed transcranial stimulation system for cognitive enhancement HRL Laboratories Inc. Identifying target regions and delivering TMS while encoding memories or asleep to promote learning. Table 9: Patents describing neuromodulation techniques directed at cognitive enhancement in healthy populations. Seven percent (7%) of collected patents are assigned to branch of subgroups reserved for the evaluation of psychological states, also labeled as psychotechnics (Table 10). The dominant bottom-level code, A61B5/165, identified 4% (N=35/779) of patents and described methods of assessing a state of mind or evaluating feelings such as depression or anxiety. Mental health management represents a key theme among A61B5/165 patents; Many are diagnostic tools. For example, US Patent No. 10,238,329, owned by Columbia University, encompasses a method of diagnosing attention-deficit hyperactivity disorder, bipolar disorder, schizophrenia, and 40 depression with structural magnetic resonance (Bansal & Peterson, 2019). Others have recreational uses. US Patent No. 10,252,058, discloses a wearable, EEG-equipped device programmed to sense feelings of stress in a user and provide suggestions for healthy behavioural management (Fuerst, 2019). Its owner is a neurotherapy startup based in Israel called Eco-Fusion. One (N=1) patent diverges from therapy. Awarded to two Singapore-based inventors, US Patent No. 10,155,113 describes a wearable, closed-loop, transcutaneous, trigeminal neuromodulation device designed to sense drowsiness in a user and responsively provide stimulation “to keep the brain in wakefulness” (Xia & Li, 2018). No other psychotechnics subgroups represent more than 2% of the sample. 41 Subcode Abbreviated Description Frequency (%) Patents (N) A61B5/165 Evaluating state of mind 4 35 A61B5/16 Devices for psychotechnics 2 16 A61B5/163 Eye-tracking 1 9 A61B5/168 Attention-deficit and hyperactivity assessment 1 7 A61B5/162 Reaction time tests 1 4 A61B5/167 Personality evaluation 1 4 A61B5/18 Psychotechnics for vehicle drivers 0 1 A61B5/161 Flicker fusion tests 0 0 A61B5/164 Lie detection 0 0 Table 10: Prevalence of patents assigned to CPC subgroup A61B5/16 and its child nodes for psychotechnics. Three percent (3%, N=21/779) of patents bear the subcode G06F3/015, indicating methods of using nervous system activity as input for user-computer interactions, or BCI. Of these N=6 also correspond to subcode G06F2203/011 for their use of brain-based signals representing emotion or mood as input in user-computer interactions (Table 11). Four (N=4) interrelated patents owned by Meta describe methods of manipulating VR scenes in response to users’ cognitive processes (Mullins, 2016a, 2016b, 2018a, 2018b). Another owned by San Diego State University describes a DBS device designed to communicate with other medical implants and treat neurologic disorders (Kee et al., 2019). The sixth, owned by IBM, outlines a method of 42 expediting internet searches by prioritizing results previously selected under similar emotional or physical conditions (Chefalas et al., 2020). 43 US Patent No. Title Owner Brief Description 9,354,702 Manipulation of virtual object in augmented reality via thought Meta Platforms Technologies LLC Identifying an object of thought represented by neural activity and rendering it in a virtual landscape. 9,383,819 Manipulation of virtual object in augmented reality via intent Meta Platforms Technologies LLC Identifying a mental objective represented by neural activity and rendering it in a virtual landscape. 9,996,155 Manipulation of virtual object in augmented reality via thought Meta Platforms Technologies LLC Transforming objects in a virtual landscape in response to neural activity. 9,996,983 Manipulation of virtual object in augmented reality via intent Meta Platforms Technologies LLC Identifying a mental objective represented by eye movement and neural activity and rendering it in a virtual landscape. 10,452,143 Apparatus and method of implantable bidirectional wireless neural recording and stimulation San Diego State University Research Foundation Treating neurologic and spinal disorders with an implantable, closed-loop, neurostimulation system. 10,810,270 Web search based on browsing history and emotional state International Business Machines Corporation (IBM) Narrowing internet search results to sites previously visited in a specific state of mind. Table 11: Descriptions of patents assigned to CPC subgroup G06F2203/011 for emotion or mood input in user-computer interactions. One percent (1%, N=4/779) of patents coded to subgroup G06N20/00 highlight applications of ML in neurotechnology (Table 12). Two (N=2) apply ML to medical practice, the 44 first in treatment delivery and the second in treatment planning (Lujan et al., 2019; Strahl et al., 2019). A third is recreational, applying ML to identify and associate patterns of neural activity with music playlists (Chong & Zhang, 2016). The listed owner, FutureWei Technologies, is a private R&D firm committed to Open Innovation frameworks. The fourth patent, owned by private BCI development firm Arctop Ltd., combines neuroimaging and ML in the context of security and authentication (Furman & Kwalwasser, 2020). US Patent No. Title Owner Novel Application of Machine Learning 10,327,654 Detecting neuronal action potentials using a sparse signal representation Med-El Elektromedizinische Geräte Gesellschaft GmbH Optimizing feedback measurements and performance in cochlear implants. 10,360,511 System and method to estimate region of tissue activation The Cleveland Clinic Foundation Simulating nervous tissue responses based on varying stimulation parameters. 10,482,124 Music recommendation based on biometric and motion sensors on mobile device FutureWei Technologies Inc. Processing biometric data to generate personalized music recommendations. 10,706,134 Method and system for providing a brain computer interface Arctop Ltd. Registering and authenticating users based on a “neural fingerprint.” Table 12: Descriptions of novel applications of machine learning in patents assigned to CPC group G06N20/00. Four percent (4%, N=31/779) of patents reference CPC subclass codes associated with commercial and recreational technology (Table 13). Educational tools and techniques are the most prevalent non-medical applications of neurotechnology examined, represented by subclass code G09B and spanning N=12 patents examined. These patents predominantly outline methods for training social and cognitive abilities like speech, empathy, and emotional attentiveness. The 45 second-most prevalent non-medical application, commerce, is identified by subclass code G06Q. Eleven (N=11) commerce-linked patents integrate neurotechnology with business and finance, often aiming to study or manipulate neurologic correlated of consumer behaviour. Communication, represented by the subclass code G08B, is the third-most prevalent non-medical application of neurotechnology. Only N=5 patents use neurotechnology to facilitate person-to-person or person-to-machine communication. Applications of neurotechnology in athletic training and video games, denoted by sub-class codes A63B and A63F, respectively, are each outlined in N=4 patents. Year Granted G09B: Education (N) G06Q: Commerce (N) G08B: Communication (N) A63B: Athletic Training (N) A63F: Video Games (N) 2016 1 1 0 0 0 2017 7 1 1 1 1 2018 2 2 2 1 1 2019 0 2 2 1 2 2020 2 5 0 1 0 Total 12 11 5 4 4 Table 13: Annual sums of newly granted patents referencing CPC codes associated with non-medical industries. Neurotechnology techniques assigned to subclass G06Q for commerce utilize neuroimaging to evaluate consumer behaviours or conditions. Eleven (N=11) are described in Table 14. Four (N=4) interrelated patents owned by Allstate Insurance outline similar methods of monitoring biometric data to determine safety hazards and calculate insurance premiums (Manzella & Ismaili, 2019a, 2019b, 2019c). Three (N=3) under the ownership of industrial 46 research firms SBB Research and Nielsen encompass neuromarketing services for optimizing consumer appeal of media pieces (Pradeep et al., 2018, 2020; Samuel & Moran, 2016). Similarly, US Patent No. 9,808,709 held by Playnovation provides methods of studying user behaviours and neural profiles to better target advertisements (Brown & Cozad, 2016). This patent specifically describes extracting neural activity in VR environments. The remaining patents each deal in a different industry. Applied for and owned by individual inventors rather than a corporation, US Patent No. 10,664,904 adapts neurotechnology to build financial management skills and help curb purchasing (Wright & Wright-Freeman, 2020). US Patent No. 10,810,270 describes a process of filtering internet searches according to emotional and physical conditions of a user (Chefalas et al., 2020). Finally, US Patent No. 10,851,416, describes a commercial diagnostic service for neurologic illness akin to the DNA testing services offered by commercial firms such as AncestryDNA and 23andMe (Rice, 2020). The owner, Likeminds, includes in the specifications its intention to sell access to customer data to interested third parties. 47 US Patent No. Title Owner Brief Description 9,280,784 Method for measuring engagement SBB Research Group LLC Determining consumer interest in and engagement with media from neural activity. 9,808,709 System and methods for biometric detection of play states, intrinsic motivators, play types/patterns and play personalities Playnovation LLC Categorizing users according to neural and behavioural patterns and matching them with products and services. 9,973,834 Communication system and method for using human telematic data to provide a hazard alarm/notification message to a user in a static environment such as in or around buildings or other structures Allstate Insurance Co. Monitoring biometric and environmental conditions in to alert users or emergency services of unsafe conditions. 10,127,572 Stimulus placement system using subject neuro-response measurements The Nielsen Co. Determining advertisement and entertainment effectiveness from neural activity and suggesting further media. 10,424,023 System and method of determining an insurance premium quote based on human telematic data and structure related telematic data Allstate Insurance Co. Monitoring biometric and environmental conditions to calculate insurance premiums for buildings. 10,425,705 Communication system and method for using human telematic data to provide a hazard alarm/notification message to a user in a static environment such as in or around buildings or other structures Allstate Insurance Co. Monitoring biometric and environmental conditions to calculate measurements of user safety. 10,643,287 System and method for determining an insurance premium based on analysis of human telematic data and vehicle telematic data Allstate Insurance Co. Monitoring biometric and environmental conditions to calculate insurance premiums for vehicles. 10,664,904 System, device and method for detecting and monitoring a biological stress response for financial rules behavior Daphne Wright and Kayla Wright-Freeman Detecting and alerting users to physiological signs of stress concurrent to purchasing behaviours. 10,679,241 Analysis of marketing and entertainment effectiveness using central nervous system, autonomic nervous system, and effector data The Nielsen Co. Determining effectiveness of advertising or entertainment from multiple imaging modalities. 10,810,270 Web search based on browsing history and emotional state IBM Corp. Narrowing internet search results to sites previously visited in a specific state of mind, geographic location, or on a specific device. 10,851,416 Predictive neurodiagnostic methods Likeminds Inc. Generating individualized risk profiles based on medical history, environmental exposure, biological markers, and behavioral data. Table 14: Descriptions of neurotechnology patents assigned to CPC subclass G06Q for commerce. 48 4.3 Ethical Analysis Implementation of the ethics analysis logic model resulted in N=39 patents assessed quantitatively, N=21 recommended for expert validation, and N=9 selected for in-depth exploration (Table 15). Of these, N=4 raised concerns for scientific validity, N=3 for mental privacy, and N=2 for mental integrity. Scientific validity: Four (N=4) patents are assigned to concerns for scientific validity. First, US Patent No. 9,956,425 provides a method of delivering photodynamic therapy to injured neurons, particularly those involved in sight (Peyman, 2018). It entails two steps: an optogenetic technique for inducing rhodopsin expression in nervous tissue followed by implantation and operation of a fiber optic neurostimulator. Twenty-seven (27) references to peer-reviewed publications in optogenetics and neuroscience demonstrate a clear, logical progression from the scientific principles supported by research to the therapeutic mechanisms of the proposed neurointervention. US Patent No. 10,512,769, which claims applications of non-invasive vagus nerve stimulation (VNS) in behavioural disorder management (Simon et al., 2019). In this patent, 67 references to scientific papers explicate the mechanisms and clinical benefits of non-invasive cranial nerve stimulation, converging on essential features of the accompanying disclosure. Third, US Patent No. 10,154,812 broadly encompasses methods of “affecting living tissue,” “interpreting brain patterns and structures,” and “interpreting and manipulating brain signals” (Howard, 2018; 25.40-26.50). Of its 5 referenced papers, only one was published within the decade preceding application submission. US Patent No. 10,396,905 delineates methods of communicating cognitive states from one mind to another using transcranial focused ultrasound stimulation, or tFUS (Tyler et al., 2019). Its claims involve encoding information in acoustic 49 waves and transmitting pulses to the brain of a recipient such that the information is perceived. Although the 14 works of peer-reviewed literature it cites are contemporaneous, their focus on neurophysiology is only sufficient to link tFUS to changes in neuronal activity. No evidence is provided to substantiate the claimed methods of encoding or reproducing cognitive states. 50 US Patent No. Title Owner Primary Ethics Concern Brief Description 9,956,425 Methods to regulate polarization and enhance function of cells Dr. Gohlam Peyman Scientific validity Delivering photostimulation to optic nerves following optogenetic treatment. 10,154,812 System, method, and applications of using the fundamental code unit and brain language Dr. Howard Newton Scientific validity Applying the Fundamental Code Unit theory to diagnose or treat neurologic disorders. 10,396,905 Method and system for direct communication Cerevast Medical Inc. Scientific validity Encoding and transmitting information in the form of ultrasound energy such that the recipient comprehends the initial message. 10,512,769 Non-invasive magnetic or electrical nerve stimulation to treat or prevent autism spectrum disorders and other disorders of psychological development ElectroCore Inc. Scientific validity Treating behavioural disorders with non-invasive vagus nerve stimulation. 9,280,784 Method for measuring engagement SBB Research Group LLC Mental privacy Determining consumer interest in and engagement with media from neural activity. 10,321,870 Method and system for behavioral monitoring Ramot at Tel-Aviv University Ltd. Mental privacy Interpreting emotional states from neural and smartphone activity records. 10,799,140 System and method for instructing a behavior change in a user Emotiv Inc. Mental privacy Teaching skills and generating advertisements with a head-mounted neurofeedback device. 9,352,145 Methods and systems for treating a psychotic disorder Boston Scientific Neuromodulation Corp. Mental integrity Treating behavioural symptoms of psychiatric disorders with deep brain stimulation. 10,155,114 Systems and methods of treating a neurological disorder in a patient Dr. Dirk DeRidder Mental integrity Treating neurologic disorders with neurostimulation in reward centres of the brain. Table 15: Neurotechnology patents coded for ethics concerns. 51 Mental privacy: Concerns for privacy arise in three patents. US Patent No. 9,280,784 describes a method for marketing that uses recorded neural activity in a participant while viewing media such as an advertisement or film (Samuel & Moran, 2016). The method continues to analyze data and estimate measurements of participant engagement or interest linked to specific stimuli or timestamps. As for psychiatric treatment, US Patent No. 10,321,870, discloses a method of comparing neural activity with smartphone data in real-time to infer a user’s psychiatric wellbeing (Nevo et al., 2019). In some cases, the method may involve alerting medical services to an abnormal evaluation result. The recreational neurotechnology technique raising privacy concerns is described in US Patent No. 10,799,140. The patent outlines a method of remotely operating a biofeedback headset to teach users skills, suggest changes in their environments, and advertise third-party products or services (Le & Mackellar, 2020). In this case, advertisement generation is informed by neural and behavioural data collected through operation of the device. Mental integrity: Patents describing DBS for psychiatric disorders raised concerns for mental integrity. US Patent No. 9,352,145 discloses a method of using implanted devices to stimulate “one or more of a frontal lobe, temporal lobe, cingulate gyrus, substantia nigra, thalamus, amygdala, hippocampus, ventral tegmental area, nucleus accumbens, and locus coeruleus” to treat “a psychotic disorder comprising at least one of schizophrenia, a delusional disorder, a schizoaffective disorder” (Whitehurst & Jaax, 2016). Likewise, US. Patent No. 10,155,114 claims a method of presenting “a first external stimulus… concurrently with electrical stimulation of a reward-related location within the brain of the patient” to treat neurologic disorders ranging from attention-deficit hyperactivity disorder, substance use 52 disorders, and autism spectrum disorder to chronic pain, schizophrenia, and “aggressive behavior” (De Ridder, 2018). 4.4 Summary The most prominent CPC designations relate to neuromodulation such as DBS for psychiatric conditions, pain, and movement disorders. Less prevalent subgroups reveal neurotechnology related to psychotechnics, BCI, machine learning, and commerce. Ethical analysis highlights a small but substantial set of patents with concerns for scientific validity, mental privacy, and mental integrity. 53 Chapter 5: Discussion In this research, I developed a novel method of characterizing technical and ethical themes in the neurotechnology patent landscape. I found an emphasis on neuromodulation, as well as many nonmedical uses of neuroimaging. I also identified a small set of patents with important neuroethical concerns in the context of innovation. Here, I describe the connections between characteristics of the patent landscape and neuroethics scholarship as well as their significance for society. I begin by discussing prominent technical themes and their meanings for healthcare, followed by an in-depth review of patents associated with other highlighted CPC designations. Then, I shift from technical to ethical with an assessment of patents tied to tensions in neurorights. I conclude this chapter with some limitations and a summary. 5.1 Major Classifications The semantic search algorithm used to collect neurotechnology patents from the online repository identified a broad range of new techniques for observing and influencing activity within the nervous system. The number of patents issued annually and the recency of their initial applications are generally consistent with reports of an expanding industry hampered by a bottleneck at the patent office. First, the positive net change in patents estimated to be issued annually (Table 5) aligns with findings in BCI patent applications of growing innovation landscapes (Greenberg et al., 2021). Although the growth rate of patent issuances is lower than that of patent applications, the difference may be attributed to a combination of application abandonment and long waits at the patent office. Regarding the latter, the average time elapsed for patents in this sample between application and issuance matches other estimations of pendency at the USPTO (Ackerman, 2011; DeGrazia et al., 2019 ). As Figure 5 demonstrates, 54 these patents represent an innovative front spanning 2013 to 2017 and may already be incorporated in polished treatments and technological goods. With broad strokes, the identities and prevalence of different subclasses assigned to patents form a technical ecosystem continuous with the larger medical industry. The clear prominence of therapeutic neuromodulation indicated by A61N represents a leading area of innovation (Table 6). As well, neuroimaging identified by A61B also encompasses a majority of the sample, speaking to a secondary area of diagnostics and neurologic assessments. The remaining major subclasses pertain directly to either medical practice or crucial mechanisms of neurotechnology, together offering no indication of departure from medical innovation. The minimum possible overlap between subclasses A61N and A61B was N=218, or 28% of the sample. This implies a latent yet substantial emphasis on methods combining neuromodulation and assessment, which could represent feedback mechanisms. However, data at this level of aggregation cannot provide further detail. Examining group assignments within the largest subclass adds another important characteristic; patents referencing electrotherapy are far more abundant than any other group. However, so many potential embodiments of electrotherapy require many additional tiers of detail. Other forms of neuromodulation appear as peripheral fields of innovation. Bottom-level subgroup assignments in neuromodulation methods identify therapeutic innovations by both invasiveness and target condition. These data show far more invasive than non-invasive methods of electrotherapy are in the patent record. Rather than an indication of slow progress in transcranial techniques, this may reflect the lower commercial value of non-invasive neuromodulation methods patents. Although US healthcare providers are generally 55 immune from infringement suits, manufacturers are still exposed to risk (Anderson, 2019). Methods claims outlining invasive neuromodulation treatments may also encompass steps of preoperational planning and surgical implantation, necessitating specialized hardware that manufacturers must license to safely produce and distribute. In contrast, non-invasive neuromodulation treatments may require fewer additional components. Developers may be less incentivized to patent non-invasive procedures due to diminished opportunities to enforce their exclusive rights. An unenforceable patent has no direct commercial value (Devlin, 2009). However, these patents are still granted and published by an issuing authority. They may therefore serve as advertisements of developers’ innovativeness or commercial-mindedness, attracting industry partners (Long, 2002). Therefore, a full picture of the commercial ecosystem is needed to understand the disparity between invasive and non-invasive neuromodulation methods. Regarding individual subgroups, dominance of A61N1/36082 over other treatment-oriented classifications points to an emphasis on developing implantable neurotechnology treatments for disorders of the mind (Table 7). Yet rather than representing a broad push toward psychiatric interventions, the prevalence A61N1/36082 may instead reflect widespread interest in developing advanced treatments for neurodegenerative disorders and their mental sequelae. This aligns more closely with the established use of DBS for symptom management in Parkinson’s disease as well as its still experimental applications in the context of Alzheimer’s disease (Cury et al., 2022; Hartmann et al., 2019; Ning et al., 2022). Differences in the numbers of patents dually assigned to A61N1/36082 and other subgroups may support this connection. Two treatment-linked subgroups appear in the sample with similar prevalence: A61N1/36067 for movement disorders and A61N1/36071 for pain (Table 7). Despite their similar sizes, 53 patents 56 are assigned subgroup codes for both movement disorders and cognitive or psychiatric disorders, while only 19 patents are assigned codes for both pain disorders and cognitive or psychiatric disorders. Such a large difference may be rooted in an emphasis on developing flexible interventions for managing motor and cognitive or psychiatric symptoms, which are strongly associated with neurodegenerative diseases (Ning et al., 2022). Treatment-linked subgroups for disorders of mood, eating, and substance use appear most often alongside their parent node, A61N1/36082. This practice may identify non-limiting qualities, or characteristics encompassed by proprietary rights that are not essential to the invention at hand (Schmoch & Khan, 2019). In other terms, licensees may use these patented methods to treat any of the conditions mentioned without overstepping their proprietary rights. Ultimately, these findings demonstrate that a bottom-up approach to landscape characterization can outline prominent areas of innovation. Still, ambiguous classifiers may limit interpretability. An understanding of both the broader patent ecosystem and the data reflecting classification distribution are needed to contextualize these trends. 5.2 Landscape Themes Advancements in neurotechnology interventions for psychiatric conditions make up the most prominent treatment-linked subgroup in the sample. In-depth review of disclosures reveals over half of patents within the subgroup exclusively target cognitive dysfunction. In cases where psychiatric dysfunction is within scope, responsiveness to patient intention and state-of-mind is a common theme (Table 8). On one hand, monitoring mental conditions via neurologic signal generally raises concerns for mental privacy (McStay, 2020). On the other, biomedical ethics and regulatory legal 57 frameworks broadly prohibit the use of experimental or invasive neurointerventions in patients so long as less severe alternatives are available (Morgan et al., 2015). Therefore, barring cases of potentially criminal malpractice, it stands to reason that the benefits anticipated for quality of life would far outweigh the more indirect risks of compromised privacy (Shlobin & Rosenow, 2022). Concerns for mental integrity are relevant insofar as malicious hacking may cause profound harm. Otherwise, these forms of cognitive and psychiatric neuromodulation appear to uphold the individual’s neurorights, preserving the self beyond the body’s natural capacity. Treatment may, for example, slow the progression of Alzheimer’s disease, reducing the pace at which symptoms of amnesia and personality change manifest. In such a case, restricting access to neurotechnology would amount to a violation of fundamental rights to life, liberty, and personal security. This links to humanitarian obligations in post-clinical trial care, which is another theme in biomedical and neuroethics (Eaton et al., 2015; Tubig & Gilbert, 2023). One surprising characteristic identified among patented psychiatric inventions is the ability of the device to respond to patient intentions (Table 8). Many scholars who write about DBS and self-agency cite a potential tension between the emotions a person would normally feel and the emotions DBS causes them to feel (Aggarwal & Chugh, 2020; Bluhm & Cabrera, 2022; Schönau et al., 2021). For example, Goering et al. (2017) describe a patient receiving DBS treatment for depression who attended a funeral after having her settings programmed. Upon finding herself unable to cry, the patient recalled feeling alienated from her own body and mind. However, integration of intention-sensitive technology into DBS may mitigate this concern by allowing patients to pause treatment in response to situational demands, thereby promoting feelings of personal agency. 58 Two (N=2) patents propose DBS treatment for SUD, one filed by an applicant in China and the other by a branch of the Saudi Arabian government, raising tensions in both the contexts of research ethics and human rights. Long-term safety has not been established, and potential harms remain far more compelling than benefits (Carter & Hall, 2011; Clausen, 2010). With many socioeconomic extensions, SUD often affects members of vulnerable or marginalized populations (Johnson & Chamberlain, 2008). Coercion to patriciate in trials and equitable access to treatment are of heightened concern (Boyle & Illes, 2023). These tensions intersect with broader discussions of international differences between ethics standards raised by human gene editing and whole-body transplantation (de Lecuona et al., 2017; Iltis, 2022). Psychotechnics patents encompass a small portion of the sample and primarily describe psychiatric neuroimaging techniques or DTC neurotechnology for promoting user mindfulness and health. Psychiatric neuroimaging is an emerging field promising to replace subjective evaluations with objective diagnostic tools, permitting earlier disease detection and intervention (Nour et al., 2022). However, neurobiology is only one component of psychiatric health. Social factors such as secure housing and access to food also have major influences on individual wellbeing and brain development (Barch & Luby, 2023; Ferschmann et al., 2022). Neuroimaging cannot identify these factors. Therefore, overreliance on neurologic indicators of health may fail to address the broader conditions from which diseases emerge. Of further concern are training biases, inequitable access, and psychological harms resulting from automated and potentially unwanted diagnoses (Martinez-Martin et al., 2018). Although neuroethics scholarship is already closely tied to this field, partnerships with development firms may not be established. The same is true of DTC neurotechnology firms, which face fewer regulations surrounding data use 59 (Dasgupta, 2019; Dasgupta, 2020). Last, although lie detection may remain an active area, no evidence of continued interest was available through the analyses conducted here. With only N=5 patents modulating memory and learning processes and healthy adults, evidence cannot be ascertained for widespread research and development of cognition enhancing neurotechnology. Rather, the involvement of two key entities may suppress commercial development in this field. DARPA’s role in researching transcranial neuromodulation for memory enhancement reveals interests of the US military. Patent rights reserved by the US government suggest access to any resulting products may be highly limited for the foreseeable future (Farley & Isaacs, 2020). In addition, any eventual transfer to civilian use will likely place restrictions on commercialization, leading to unforeseeable limitations in functionality. Whereas neither the US government nor its contractors may opt to pursue infringement claims against DTC neurotechnology firms, such litigation is in fact the speciality of Elwha owner Intellectual Ventures. Described in literature as “particularly dangerous” and “the über troll,” Intellectual Ventures owns over 75,000 patents, 2,000 shell holding companies, and has launched more litigations over more patents than any other firm on the record (Oliver et al., 2016; Seidenberg, 2006; Smith, 2014; Teska, 2011). Given the breadth its patents cover, the simple presence of Intellectual Ventures may strongly discourage others from entering the field. It is also possible that Intellectual Ventures may license the patents to a practicing entity for commercial development. Even in this case, the expense of licensing fees may impose a significant barrier to entry, and access would be restricted to only a narrow range of firms (Duchêne & Serfes, 2012). Thus, pressures in the IP marketplace may restrict development of DTC cognitive enhancement technology for years to come. 60 Very few patents in the sample analyze neurologic information to support BCI. Among these, even fewer involve drawing inferences as to users’ emotional and cognitive states. Four (N=4) patents owned by Meta depict a commercial strategy designed to expand opportunities for the highly publicized VR platform known as the Metaverse. Records indicate that Meta—known at the time as Facebook—acquired the patent cluster from a network of non-practicing entities in mid-2021, only two months before publicly rebranding and announcing its metaverse project (Tam, 2022). These patents are not a guarantee that the incipient Metaverse will eventually collect, study, and act on users’ internal feelings and beliefs, but it is certainly a warning of what may come. This is particularly concerning given Meta’s exceptionally poor reputation for accountability and data stewardship. In 2016, the decision made by still-serving executives to sell identifying information belonging to millions of platform users directly impacted election outcomes across Canada, the US, and the United Kingdom, and is today considered a watershed moment in digital culture (Isaak & Hanna, 2018). The severity of Meta’s transgression more than justifies heavy scrutiny, and their investments in neurotechnology ought not go unnoticed. Neither of the two remaining patents taking emotion-based input raise unique concerns. One facilitating connection between two neuroprostheses implanted in a single patient may indeed benefit users by digitally restoring neuronal pathways necessary for certain cognitive states. Potential harms are largely akin to those associated with cognitive or psychiatric DBS treatment, which were already described. The internet search method proposed by the second patent primarily raises concerns for privacy but seems much too inconvenient compared to current predictive search engines to ever manifest. In this sample, ML contributes to neurotechnology across three different industries: healthcare, entertainment, and security (Table 12). In each, ML techniques are intended to learn 61 from neurologic activity and develop predictions based upon it, with one even using predictions to drive electrostimulation in a closed-loop neuroprosthesis. However, the concerns linked to cochlear stimulation are far afield from DBS. Literature surrounding ethics implications of ML-equipped neurotechnology does not identify cochlear stimulation within their scope of concern (Farisco et al., 2022; Friedrich et al., 2021; Ienca, 2021) All of the methods described by these patents are notably low risk. Even concerns for privacy seem minimal. Two of these inventions deal with data protected by regulations; the third belongs to a firm founded on Open Science principles, and the fourth is itself a security system. For the latter, privacy is its raison d'être. The sum of ML-driven neurotechnology patents in this sample is far lower than predictions based on trends in patent applications in the same time period and technical synergy between the fields (Abadi & Pecht, 2020). Moreover, only two subgroups descend from the ML group classification. This is far fewer than would be expected for such a complex and commercially viable field of innovation. As a recently established field, the true breadth of advancements in ML may be coded diffusely across a wide range of CPC designations, requiring alternative semantic operators to appropriately search and visualize (Hötte et al., 2022). Some who have studied the distribution of ML-linked CPC codes argue that classification sprawl necessitates codebook maintenance (Thielmann et al., 2021; Toole et al., 2020). Recent escalation in the rate of expansion of commercial ML technology may catalyze this step, but tracking advances in ML-integrated neurotechnology will remain a challenge for the foreseeable future. Only a small number of patents in the sample are assigned subclass codes for extra-medical subject matter (Table 13). Most involve DTC neurotechnology with EEG interfaces, raising privacy concerns related to secondary uses of brain-based data (Ryberg, 2017). 62 Educational tools generally comprise DTC neurotechnology systems designed to help users build fundamental social abilities. Successful development and commercial rollout could immensely benefit individuals who suffer from social deficits and have limited access to occupational therapy. Commercial applications of neurotechnology show a sustained increase in patent issuances per year but cannot stand alone as evidence of any broader trend. Their subset of patents described a range of methods of turning brain-based data into profit, including optimizing advertisement efficacy based on data representing entertainment and outright selling customers’ medical records. Also in this subset, two clusters of inventions may signal a deeply problematic shift in the commercial landscape facilitated by neurotechnology. The first pertaining to neuromarketing highlights an industry solely purposed to maximize bias in decision-making (Sieber, 2019). It may be acceptable to use neuroscience techniques to elucidate the dos and don’ts of advertising, but the incredible numbers and diversity of clientele suggest a value surpassing public knowledge. Second, the Allstate cluster points to concerning developments in actuarial science and the insurance industry where submission of private, brain-based data may be required for access to services or rewarded with discounts, and meeting if not approaching criteria for coercion. Ultimately, none of the patents characterized here necessarily raise tensions for human rights values. However, the logical leap from use as intended to ethics violations is much shorter for some than others. Specifically, certain international interests in DBS for SUD may at face value draw from neurotechnology literature—the concept has been widely discussed for some time—but situated within current sociopolitical contexts, the implications for people in China and Saudi Arabia living with SUD are chilling. Why these neurointerventions require US patents is also of note, as it implies their owners’ intentions to pursue commercialization within the US 63 or exclude others from the same. In all other patented therapies, the greatest human rights concerns arise from the prospect of clinical trials and the obligation of trial runners to uphold participants’ rights to health and personal integrity upon trial cessation (Eaton et al., 2015). Beyond medicine, Meta’s venture into recreational BCI should draw particular scrutiny from privacy watchdogs, though not at the cost of ignoring other operators in the field. Last, considering the complex relationship between insurance firms and ethics, Allstate’s investment in BCI and the consequent risks for privacy and fairness may represent a point where opportunities for soft law end and policymaker engagement become necessary. 5.3 Ethics Themes Ethical analysis captured only a small portion of the neurotechnology patent record. Identified themes include scientific validity, mental privacy, and mental integrity (Table 15). No highlighted patents are linked to concerns for cognitive integrity or continuity of personality. Scientific validity: While we expected that the assessment of scientific validity would be straightforward, two of the patents coded as scientifically doubtful contained bibliographies grounding claims in relevant contemporary research that, at least, imply technical merit. However, US Patent No. 10,512,769 described other embodiments in its disclosure which were not supported: “in another aspect of the invention, [VNS] is performed on a pregnant woman, preferably during the first trimester, in order to prevent abnormal neurodevelopment of the fetus… it may also be useful for women who may pass on an autism gene variant to her child” (Simon et al., 2019). No evidence links VNS to fetal development or genetic transmission. The two remaining patents provide only weak support for their claims. Four (4) of the 5 peer-reviewed publications cited by US Patent 64 No. 10,154,812 predate the application date by over a decade. In contrast, US Patent No. 10,396,905 cites recent advances in science, but none of its citations substantiate its claims about thought extraction and implantation (Tyler et al., 2019). Mental privacy: Similar to concerns for scientific validity, the broader commercial and clinical contexts limit concerns for mental privacy. US Patent No. 9,280,784 covers, in essence, a research method in which consent is virtually necessary for participation (Samuel & Moran, 2016). Although informed consent is a step further, such detail would not be included in the patent document. US Patent No. 10,321,870 provides a method of analysis directed at both brain-based data and smartphone activity (Nevo et al., 2019). Certainly, these would constitute intrusive measures in any healthy individual. Here instead, the subjects described within the patent include patients receiving treatment for psychiatric conditions or SUD. Because mental privacy is considered a relative right, circumstances in which the patient poses harm to another individual may justify its restriction (Ienca & Andorno, 2017). The last of the mental privacy-linked patents, US Patent No. 10,799,140, would theoretically collect a broad range of brain-based data with many potential secondary uses (Le & Mackellar, 2020). Poor data stewardship could expose personal identifiers, violating privacy obligations to the customer. Reflecting on recent history, the Cambridge Analytica scandal of 2016 demonstrates how user data merely representing online activity may be exploited to manipulate vast populations and direct the flow of political power (Isaak & Hanna, 2018). Some wonder what more a similarly intentioned actor could accomplish with records of individuals’ neural activity (Ienca et al., 2018). Fortunately, such a situation is unlikely to stem from this patent. The owner, Emotiv, maintains an exceptionally rigorous privacy scheme by industry standards, taking measures such as encrypting all user data, permitting users to withdraw their 65 data from proprietary servers, and conducting audits to ensure internal compliance (Steinhagen & Kettani, 2020). Thus, brain-based data stored in private Emotiv servers may be more secure than those stored by their competitors. Mental integrity: Associated patents outline invasive neuromodulation treatments for different psychiatric illnesses. Their direct effects on the human mind raise unresolved tensions for patients’ rights and wellbeing, imposing a uniquely stiff barrier to their implementation (Ienca & Andorno, 2017). In the case of US Patent No. 9,352,145, neuromodulation aims to alleviate the symptoms of psychotic disorders (Whitehurst & Jaax, 2016). This entails adjusting neural activity with the net effect of changing patient experience, cutting to the core of the mind-brain relationship (Hartwich & Boeker, 2018). With so much still unknown about the emergent properties of interconnected brain regions, interventions targeting any of the regions identified by the patent may induce profound and unwanted changes in cognition and in doing so deviate drastically from the restorative aims of treatment (Brenninkmeijer, 2010). Until such time that the effects and risks of DBS for psychotic disorders in human patients are better characterized, the sheer span of uncertainties associated with the many outlined embodiments may contravene proposed rights to mental integrity (Ienca & Ignatiadis, 2020), current rights to security of persons (Bublitz, 2022), and the basic obligations of health care providers derived from the biomedical ethics principle of non-maleficence (Müller et al., 2022). Even so, relativist arguments may reasonably permit such interventions in extreme circumstances: for example, to prevent predictable and grievous harms from befalling others (Ienca & Andorno, 2017). The second patent associated with mental integrity, US Patent No. 10,155,114, raises similar concerns in its approach to neuromodulation targeting brain regions associated with reward assessment, problem solving, and behavioural planning, and functions subsumed by the 66 concept of free will (Al-Rodhan, 2018; De Ridder, 2018). This alone has broad implications for the fundamental neurorights principle of cognitive integrity, which calls for basic freedoms of thought and consciousness as they manifest in the brain (Ienca, 2021). However, the specific embodiment highlighted by the ethical analysis process was its proposed use as a form of aggression management in psychiatric treatment contexts. This cuts closer to the topic of mental illness and patients’ access to appropriate interventions, calling into question the rights of patients with certain neuropsychiatric disorders. Applying the greater good argument again results in extraordinary conditions where use of DBS for behavioural management would be permissible. For example, in patients with stage IV chronic traumatic encephalopathy (CTE), a progressive, neurodegenerative disease caused by repetitive brain trauma, acquired and explosive rage may require some sort of management to ensure public safety. However, advanced dementia may prohibit meaningful acquisition of consent (Gilbert, 2015). No patents are strongly associated with concerns for either proposed neurorights for cognitive liberty or psychological continuity. There are numerous conceivable reasons why this is the case. For example, commercial firms during this time span may not have been interested or willing to invest in developing potentially violating neurotechnology out of concern for reputational damage or inability to recoup costs. Similarly, evidently harmful embodiments may damage patent lawyers’ reputations, restricting future opportunities. 5.4 Limitations Of the 3,065 patents first collected, only 28% met inclusion criteria. This low return rate likely resulted from unforeseen uses of terms such as neural and deep, which frequently appeared in the contexts of neural networks and deep learning models. The prominence of 67 certain terms in other fields of innovation may have biased search algorithm construction, but the effects on results are unclear. Interpretation is an inherently subjective exercise that incorporates personal biases. Other reviewers may find distinct, yet equally valid profiles of the patents reported here. I aimed to standardize my interpretation outcomes by achieving strong interrater reliability with a patent expert. Even so, differences may remain. Issued patents may change or expire for numerous reasons. Most frequently, owners fail to recoup the initial expense and cease fee payments to prevent further losses on sunk costs. Other times, infringement litigation may annul or restrict the claims. No matter the cause, inventions described by an expired patent cannot be patented again. For patents reviewed in this study, I did not perform follow-up analyses to ensure their maintenance after the initial date of collection. Some of the patents described may no longer be active. Other limitations stem from the nature of patents as early-stage records of commercial innovations. Non-limiting embodiments allow for unanticipated but nonetheless protected products beyond those outlined in the text. However, identifying the full range of plausible outcomes for any individual disclosure presents a technical and philosophical challenge far beyond the scope of the current work. The concrete directions in which any disclosure has progressed on its path to commercial realization are also unavailable to the public. Patent holders may award licenses to as many merchants as they wish, creating disconnect between the prevalence of any theme within the patent landscape and its eventual prevalence in the marketplace. Additionally, commercial goods may not use patented technology in their construction. These factors limit the predictive value of the patent record but do not detract from its existence as the sole record of upcoming products. 68 5.5 Summary Within the innovation landscape studied, neurotechnology plays a predominantly medical role. However, opportunities for misuse provoke concerns for user or patient autonomy and wellbeing. These concerns center around the scientific validity of the patented subject matter and mental privacy and integrity. Although an opportunity is far from a guarantee, neurotechnology is too critical to leave even the slightest risk unaddressed. Study of the patent record reveals risks associated with upcoming neurotechnology products and directs neuroethicists toward important issues and actors in the innovation landscape. 69 Chapter 6: Conclusion I begin my final chapter with a summary of my research, then discuss opportunities for further research. 6.1 Synopsis In less than a century, neurotechnology has progressed from mysterious zigzags to methods of curing disease, powering robotic arms, and decoding the contents of thought (Chandler et al., 2022; Lee et al., 2009). As much of the world faces ongoing social and public health crises, many wealthy nations have dedicated vast sums to develop technology-based solutions, in turn driving their rapid diffusion and explosive industrial growth (Gaudry et al., 2021). The mind becomes ever more accessible, and new opportunities to exploit, manipulate, or otherwise cause harm with these tools regularly emerge (Illes & Bird, 2006). Preserving the promise of neurotechnology requires a culture of thoughtfulness and responsibility among its users and developers alike (Pfotenhauer et al., 2021). These reasons compel neuroethicists to build partnerships with stakeholders, understand their needs, and coordinate value-driven practices (Garden et al., 2019). Although partnerships should begin as early as possible, the first and most important stages of commercial ventures have only recently been addressed (Roskams-Edris et al., 2017; Spranger, 2023). Here, I have provided a broad account of neurotechnology innovation as reflected by methods patents issued by the USPTO between 1 January 2016 and 31 December 2020. Using the CPC scheme, which indexes technical features of inventions, as a codebook, I drew on methods of thematic analysis to identify major fronts of innovation and conduct in-depth assessments of inventions in crucial areas. Data depict a landscape focused mainly on medical 70 innovation, with small but significant offshoots in a variety of other industries. Two patents outlining DBS for SUD were notable insofar as they were awarded to inventors in regions known widely for human rights violations. Otherwise, ethics concerns tied to patented therapeutics primarily related to clinical trial runners’ obligations toward patients as participants. Overcoming these will be key to achieving the promise of neurotechnology. Outside of medicine, the involvement of large firms in BCI innovation such as IBM, Meta, and Allstate may eventually require top-down governance approaches, but the many smaller companies in the field present ample opportunity to build ground-level neuroethics partnerships promoting responsible and value-driven development practices. In parallel, I conducted an iterative and co-constructive review of the implications of neurotechnology patents for neurorights. Very few patents were identified through this process, and concerns were generally alleviated when framed within their broader commercial contexts. However, the same may not be true of more recent issuances. Especially considering the exponential growth recorded elsewhere in neurotechnology patent applications, the time to grow neuroethics engagement with IP experts is now. 6.2 Future Directions The patent landscape remains a vast and largely unexplored resource for neuroethics initiatives studying progress and proliferation of neurotechnology. Although this study provides the most thorough analysis to date, it focused on a subset of patent activity. Future research could first consider more powerful search methodologies to better grasp the expanse of the field. For example, cutting edge, AI-driven, semantic analysis techniques may optimize search parameters and reduce streamline data collection (Setchi et al., 2021). Movement toward cohesive search 71 methodologies is crucial to permit statistical comparisons between patent analyses studying different time spans or jurisdictions. Patent applications, which were not considered in this study, should also receive greater scholarship. Analyses generally review applications rather than issuances to obtain the broadest and most up to date perspectives of commercial innovation possible (Clarke, 2018). However, applications far outnumber issuances, and those that survive the examination process virtually always undergo substantial changes (DeGrazia et al., 2019 ). Here, I focused on issuances, which are fewer in number and most likely to be realized as commercial products. The single most important factor for future research will be expert engagement. The opportunities for neuroethics in IP and vice versa have just recently been characterized, and even then, only preliminarily (Illes et al., 2019; Roskams-Edris et al., 2019; Roskams-Edris et al., 2017). Spranger (2023) lays out a foundation for an early warning system, wherein neurotechnology patents applications are automatically shared with expert neuroethicists who review the disclosure, elucidate any social concerns or ethical tensions, and cooperate with patent owners to incorporate principles of responsible innovation throughout the commercial development process. Such a system would enact a pre-emptive safety net, catching problems before they manifest in practice and reducing the likelihood of anyone undermining the promise of neurotechnology. However, it cannot be achieved by neuroethicists alone. IP law is a deeply complex field, with endless nuances that are navigable only by seasoned experts. In order to ensure proportional measures and the correct heading, neuroethics needs to expand engagement initiatives beyond innovators to also include patent lawyers, strategists, examiners, and policymakers. 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Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-ShareAlike 4.0 International
Graduate
Illes, Judy
The neurotechnology patent landscape in a time of neuroethics : 2016-2020
Text